Spatial variability of organic layer thickness and carbon stocks in mature boreal forest stands--implications and suggestions for sampling designs.

PubMed

Kristensen, Terje; Ohlson, Mikael; Bolstad, Paul; Nagy, Zoltan

2015-08-01

Accurate field measurements from inventories across fine spatial scales are critical to improve sampling designs and to increase the precision of forest C cycling modeling. By studying soils undisturbed from active forest management, this paper gives a unique insight in the naturally occurring variability of organic layer C and provides valuable references against which subsequent and future sampling schemes can be evaluated. We found that the organic layer C stocks displayed great short-range variability with spatial autocorrelation distances ranging from 0.86 up to 2.85 m. When spatial autocorrelations are known, we show that a minimum of 20 inventory samples separated by ∼5 m is needed to determine the organic layer C stock with a precision of ±0.5 kg C m(-2). Our data also demonstrates a strong relationship between the organic layer C stock and horizon thickness (R (2) ranging from 0.58 to 0.82). This relationship suggests that relatively inexpensive measurements of horizon thickness can supplement soil C sampling, by reducing the number of soil samples collected, or to enhance the spatial resolution of organic layer C mapping.

Image gathering and processing - Information and fidelity

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Halyo, N.; Samms, R. W.; Stacy, K.

1985-01-01

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

Experiments with central-limit properties of spatial samples from locally covariant random fields

USGS Publications Warehouse

Barringer, T.H.; Smith, T.E.

1992-01-01

When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Spatially intensive sampling by electrofishing for assessing longitudinal discontinuities in fish distribution in a headwater stream

USGS Publications Warehouse

Le Pichon, Céline; Tales, Évelyne; Belliard, Jérôme; Torgersen, Christian E.

2017-01-01

Spatially intensive sampling by electrofishing is proposed as a method for quantifying spatial variation in fish assemblages at multiple scales along extensive stream sections in headwater catchments. We used this method to sample fish species at 10-m2 points spaced every 20 m throughout 5 km of a headwater stream in France. The spatially intensive sampling design provided information at a spatial resolution and extent that enabled exploration of spatial heterogeneity in fish assemblage structure and aquatic habitat at multiple scales with empirical variograms and wavelet analysis. These analyses were effective for detecting scales of periodicity, trends, and discontinuities in the distribution of species in relation to tributary junctions and obstacles to fish movement. This approach to sampling riverine fishes may be useful in fisheries research and management for evaluating stream fish responses to natural and altered habitats and for identifying sites for potential restoration.

[Sampling optimization for tropical invertebrates: an example using dung beetles (Coleoptera: Scarabaeinae) in Venezuela].

PubMed

Ferrer-Paris, José Rafael; Sánchez-Mercado, Ada; Rodríguez, Jon Paul

2013-03-01

The development of efficient sampling protocols is an essential prerequisite to evaluate and identify priority conservation areas. There are f ew protocols for fauna inventory and monitoring in wide geographical scales for the tropics, where the complexity of communities and high biodiversity levels, make the implementation of efficient protocols more difficult. We proposed here a simple strategy to optimize the capture of dung beetles, applied to sampling with baited traps and generalizable to other sampling methods. We analyzed data from eight transects sampled between 2006-2008 withthe aim to develop an uniform sampling design, that allows to confidently estimate species richness, abundance and composition at wide geographical scales. We examined four characteristics of any sampling design that affect the effectiveness of the sampling effort: the number of traps, sampling duration, type and proportion of bait, and spatial arrangement of the traps along transects. We used species accumulation curves, rank-abundance plots, indicator species analysis, and multivariate correlograms. We captured 40 337 individuals (115 species/morphospecies of 23 genera). Most species were attracted by both dung and carrion, but two thirds had greater relative abundance in traps baited with human dung. Different aspects of the sampling design influenced each diversity attribute in different ways. To obtain reliable richness estimates, the number of traps was the most important aspect. Accurate abundance estimates were obtained when the sampling period was increased, while the spatial arrangement of traps was determinant to capture the species composition pattern. An optimum sampling strategy for accurate estimates of richness, abundance and diversity should: (1) set 50-70 traps to maximize the number of species detected, (2) get samples during 48-72 hours and set trap groups along the transect to reliably estimate species abundance, (3) set traps in groups of at least 10 traps to suitably record the local species composition, and (4) separate trap groups by a distance greater than 5-10km to avoid spatial autocorrelation. For the evaluation of other sampling protocols we recommend to, first, identify the elements of sampling design that could affect the sampled effort (the number of traps, sampling duration, type and proportion of bait) and their spatial distribution (spatial arrangement of the traps) and then, to evaluate how they affect richness, abundance and species composition estimates.

Accuracy Sampling Design Bias on Coarse Spatial Resolution Land Cover Data in the Great Lakes Region (United States and Canada)

EPA Science Inventory

A number of articles have investigated the impact of sampling design on remotely sensed landcover accuracy estimates. Gong and Howarth (1990) found significant differences for Kappa accuracy values when comparing purepixel sampling, stratified random sampling, and stratified sys...

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

Treesearch

Erin L. Landguth; Bradley C. Fedy; Sara J. Oyler-McCance; Andrew L. Garey; Sarah L. Emel; Matthew Mumma; Helene H. Wagner; Marie-Josee Fortin; Samuel A. Cushman

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population...

Sample design effects in landscape genetics

USGS Publications Warehouse

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

SPATIALLY-BALANCED SAMPLING OF NATURAL RESOURCES IN THE PRESENCE OF FRAME IMPERFECTIONS

EPA Science Inventory

The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. Generally, samples that are more or less evenly dispersed over the extent of the resource will be more efficient than simple rando...

Detecting spatial structures in throughfall data: the effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the numbers recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes << 200, our current knowledge about throughfall spatial variability stands on shaky ground.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

PubMed

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

Improved spatial resolution in PET scanners using sampling techniques

PubMed Central

Surti, Suleman; Scheuermann, Ryan; Werner, Matthew E.; Karp, Joel S.

2009-01-01

Increased focus towards improved detector spatial resolution in PET has led to the use of smaller crystals in some form of light sharing detector design. In this work we evaluate two sampling techniques that can be applied during calibrations for pixelated detector designs in order to improve the reconstructed spatial resolution. The inter-crystal positioning technique utilizes sub-sampling in the crystal flood map to better sample the Compton scatter events in the detector. The Compton scatter rejection technique, on the other hand, rejects those events that are located further from individual crystal centers in the flood map. We performed Monte Carlo simulations followed by measurements on two whole-body scanners for point source data. The simulations and measurements were performed for scanners using scintillators with Zeff ranging from 46.9 to 63 for LaBr3 and LYSO, respectively. Our results show that near the center of the scanner, inter-crystal positioning technique leads to a gain of about 0.5-mm in reconstructed spatial resolution (FWHM) for both scanner designs. In a small animal LYSO scanner the resolution improves from 1.9-mm to 1.6-mm with the inter-crystal technique. The Compton scatter rejection technique shows higher gains in spatial resolution but at the cost of reduction in scanner sensitivity. The inter-crystal positioning technique represents a modest acquisition software modification for an improvement in spatial resolution, but at a cost of potentially longer data correction and reconstruction times. The Compton scatter rejection technique, while also requiring a modest acquisition software change with no increased data correction and reconstruction times, will be useful in applications where the scanner sensitivity is very high and larger improvements in spatial resolution are desirable. PMID:19779586

Sampling benthic macroinvertebrates in a large flood-plain river: Considerations of study design, sample size, and cost

USGS Publications Warehouse

Bartsch, L.A.; Richardson, W.B.; Naimo, T.J.

1998-01-01

Estimation of benthic macroinvertebrate populations over large spatial scales is difficult due to the high variability in abundance and the cost of sample processing and taxonomic analysis. To determine a cost-effective, statistically powerful sample design, we conducted an exploratory study of the spatial variation of benthic macroinvertebrates in a 37 km reach of the Upper Mississippi River. We sampled benthos at 36 sites within each of two strata, contiguous backwater and channel border. Three standard ponar (525 cm(2)) grab samples were obtained at each site ('Original Design'). Analysis of variance and sampling cost of strata-wide estimates for abundance of Oligochaeta, Chironomidae, and total invertebrates showed that only one ponar sample per site ('Reduced Design') yielded essentially the same abundance estimates as the Original Design, while reducing the overall cost by 63%. A posteriori statistical power analysis (alpha = 0.05, beta = 0.20) on the Reduced Design estimated that at least 18 sites per stratum were needed to detect differences in mean abundance between contiguous backwater and channel border areas for Oligochaeta, Chironomidae, and total invertebrates. Statistical power was nearly identical for the three taxonomic groups. The abundances of several taxa of concern (e.g., Hexagenia mayflies and Musculium fingernail clams) were too spatially variable to estimate power with our method. Resampling simulations indicated that to achieve adequate sampling precision for Oligochaeta, at least 36 sample sites per stratum would be required, whereas a sampling precision of 0.2 would not be attained with any sample size for Hexagenia in channel border areas, or Chironomidae and Musculium in both strata given the variance structure of the original samples. Community-wide diversity indices (Brillouin and 1-Simpsons) increased as sample area per site increased. The backwater area had higher diversity than the channel border area. The number of sampling sites required to sample benthic macroinvertebrates during our sampling period depended on the study objective and ranged from 18 to more than 40 sites per stratum. No single sampling regime would efficiently and adequately sample all components of the macroinvertebrate community.

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

Tigers on trails: occupancy modeling for cluster sampling.

PubMed

Hines, J E; Nichols, J D; Royle, J A; MacKenzie, D I; Gopalaswamy, A M; Kumar, N Samba; Karanth, K U

2010-07-01

Occupancy modeling focuses on inference about the distribution of organisms over space, using temporal or spatial replication to allow inference about the detection process. Inference based on spatial replication strictly requires that replicates be selected randomly and with replacement, but the importance of these design requirements is not well understood. This paper focuses on an increasingly popular sampling design based on spatial replicates that are not selected randomly and that are expected to exhibit Markovian dependence. We develop two new occupancy models for data collected under this sort of design, one based on an underlying Markov model for spatial dependence and the other based on a trap response model with Markovian detections. We then simulated data under the model for Markovian spatial dependence and fit the data to standard occupancy models and to the two new models. Bias of occupancy estimates was substantial for the standard models, smaller for the new trap response model, and negligible for the new spatial process model. We also fit these models to data from a large-scale tiger occupancy survey recently conducted in Karnataka State, southwestern India. In addition to providing evidence of a positive relationship between tiger occupancy and habitat, model selection statistics and estimates strongly supported the use of the model with Markovian spatial dependence. This new model provides another tool for the decomposition of the detection process, which is sometimes needed for proper estimation and which may also permit interesting biological inferences. In addition to designs employing spatial replication, we note the likely existence of temporal Markovian dependence in many designs using temporal replication. The models developed here will be useful either directly, or with minor extensions, for these designs as well. We believe that these new models represent important additions to the suite of modeling tools now available for occupancy estimation in conservation monitoring. More generally, this work represents a contribution to the topic of cluster sampling for situations in which there is a need for specific modeling (e.g., reflecting dependence) for the distribution of the variable(s) of interest among subunits.

Biodiversity in canopy-forming algae: Structure and spatial variability of the Mediterranean Cystoseira assemblages

NASA Astrophysics Data System (ADS)

Piazzi, L.; Bonaviri, C.; Castelli, A.; Ceccherelli, G.; Costa, G.; Curini-Galletti, M.; Langeneck, J.; Manconi, R.; Montefalcone, M.; Pipitone, C.; Rosso, A.; Pinna, S.

2018-07-01

In the Mediterranean Sea, Cystoseira species are the most important canopy-forming algae in shallow rocky bottoms, hosting high biodiverse sessile and mobile communities. A large-scale study has been carried out to investigate the structure of the Cystoseira-dominated assemblages at different spatial scales and to test the hypotheses that alpha and beta diversity of the assemblages, the abundance and the structure of epiphytic macroalgae, epilithic macroalgae, sessile macroinvertebrates and mobile macroinvertebrates associated to Cystoseira beds changed among scales. A hierarchical sampling design in a total of five sites across the Mediterranean Sea (Croatia, Montenegro, Sardinia, Tuscany and Balearic Islands) was used. A total of 597 taxa associated to Cystoseira beds were identified with a mean number per sample ranging between 141.1 ± 6.6 (Tuscany) and 173.9 ± 8.5(Sardinia). A high variability at small (among samples) and large (among sites) scale was generally highlighted, but the studied assemblages showed different patterns of spatial variability. The relative importance of the different scales of spatial variability should be considered to optimize sampling designs and propose monitoring plans of this habitat.

COST-EFFECTIVE SAMPLING FOR SPATIALLY DISTRIBUTED PHENOMENA

EPA Science Inventory

Various measures of sampling plan cost and loss are developed and analyzed as they relate to a variety of multidisciplinary sampling techniques. The sampling choices examined include methods from design-based sampling, model-based sampling, and geostatistics. Graphs and tables ar...

Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

NASA Astrophysics Data System (ADS)

McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

2016-02-01

We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

PubMed Central

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-01-01

Background: The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Methods: Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Results: Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. Conclusion: This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies. PMID:26404350

Evaluation of water-quality characteristics and sampling design for streams in North Dakota, 1970–2008

USGS Publications Warehouse

Galloway, Joel M.; Vecchia, Aldo V.; Vining, Kevin C.; Densmore, Brenda K.; Lundgren, Robert F.

2012-01-01

In response to the need to examine the large amount of historic water-quality data comprehensively across North Dakota and evaluate the efficiency of the State-wide sampling programs, a study was done by the U.S. Geological Survey in cooperation with the North Dakota State Water Commission and the North Dakota Department of Health to describe the water-quality data collected for the various programs and determine an efficient State-wide sampling design for monitoring future water-quality conditions. Although data collected for the North Dakota State Water Commission High-Low Sampling Program, the North Dakota Department of Health Ambient Water-Quality Network, and other projects and programs provide valuable information on the quality of water in streams in North Dakota, the objectives vary among the programs, some of the programs overlap spatially and temporally, and the various sampling designs may not be the most efficient or relevant to the objectives of the individual programs as they have changed through time. One objective of a State-wide sampling program was to evaluate ways to describe the spatial variability of water-quality conditions across the State in the most efficient manner. Weighted least-squares regression analysis was used to relate the average absolute difference between paired downstream and upstream concentrations, expressed as a percent of the average downstream concentration, to the average absolute difference in daily flow between the downstream and upstream pairs, expressed as a percent of the average downstream flow. The analysis showed that a reasonable spatial network would consist of including the most downstream sites in large basins first, followed by the next upstream site(s) that roughly bisect the downstream flows at the first sites, followed by the next upstream site(s) that roughly bisect flows for the second sites. Sampling sites to be included in a potential State-wide network were prioritized into 3 design levels: level 1 (highest priority), level 2 (second priority), and level 3 (third priority). Given the spatial distribution and priority designation (levels 1–3) of sites in the potential spatial network, the next consideration was to determine the appropriate temporal sampling frequency to use for monitoring future water-quality conditions. The time-series model used to detect concentration trends for this report also was used to evaluate sampling designs to monitor future water-quality trends. Sampling designs were evaluated with regard to their sensitivity to detect seasonal trends that occurred during three 4-month seasons—March through June, July through October, and November through February. For the 34 level-1 sites, samples would be collected for major ions, trace metals, nutrients, bacteria, and sediment eight times per year, with samples in January, April (2 samples),May, June, July, August, and October. For the 21 level-2 sites, samples would be collected for major ions, trace metals, and nutrients six times per year (January, April, May, June, August, and October), and for the 26 level-3 sites, samples would be collected for these constituents four times per year (April, June, August, and October).

Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

NASA Astrophysics Data System (ADS)

Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

2017-09-01

The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

Analysis of spatial correlation in predictive models of forest variables that use LiDAR auxiliary information

Treesearch

F. Mauro; Vicente J. Monleon; H. Temesgen; L.A. Ruiz

2017-01-01

Accounting for spatial correlation of LiDAR model errors can improve the precision of model-based estimators. To estimate spatial correlation, sample designs that provide close observations are needed, but their implementation might be prohibitively expensive. To quantify the gains obtained by accounting for the spatial correlation of model errors, we examined (

Reducing uncertainty in dust monitoring to detect aeolian sediment transport responses to land cover change

NASA Astrophysics Data System (ADS)

Webb, N.; Chappell, A.; Van Zee, J.; Toledo, D.; Duniway, M.; Billings, B.; Tedela, N.

2017-12-01

Anthropogenic land use and land cover change (LULCC) influence global rates of wind erosion and dust emission, yet our understanding of the magnitude of the responses remains poor. Field measurements and monitoring provide essential data to resolve aeolian sediment transport patterns and assess the impacts of human land use and management intensity. Data collected in the field are also required for dust model calibration and testing, as models have become the primary tool for assessing LULCC-dust cycle interactions. However, there is considerable uncertainty in estimates of dust emission due to the spatial variability of sediment transport. Field sampling designs are currently rudimentary and considerable opportunities are available to reduce the uncertainty. Establishing the minimum detectable change is critical for measuring spatial and temporal patterns of sediment transport, detecting potential impacts of LULCC and land management, and for quantifying the uncertainty of dust model estimates. Here, we evaluate the effectiveness of common sampling designs (e.g., simple random sampling, systematic sampling) used to measure and monitor aeolian sediment transport rates. Using data from the US National Wind Erosion Research Network across diverse rangeland and cropland cover types, we demonstrate how only large changes in sediment mass flux (of the order 200% to 800%) can be detected when small sample sizes are used, crude sampling designs are implemented, or when the spatial variation is large. We then show how statistical rigour and the straightforward application of a sampling design can reduce the uncertainty and detect change in sediment transport over time and between land use and land cover types.

USING GIS TO GENERATE SPATIALLY-BALANCED RANDOM SURVEY DESIGNS FOR NATURAL RESOURCE APPLICATIONS

EPA Science Inventory

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sam...

Spatial Analysis for Monitoring Forest Health

Treesearch

Francis A. Roesch

1994-01-01

A plan for the spatial analysis for the sample design for the detection monitoring phase in the joint USDA Forest Service/EPA Forest Health Monitoring Program (FHM) in the United States is discussed. The spatial analysis procedure is intended to more quickly identify changes in forest health by providing increased sensitivity to localized changes. The procedure is...

Landsat image and sample design for water reservoirs (Rapel dam Central Chile).

PubMed

Lavanderos, L; Pozo, M E; Pattillo, C; Miranda, H

1990-01-01

Spatial heterogeneity of the Rapel reservoir surface waters is analyzed through Landsat images. The image digital counts are used with the aim or developing an aprioristic quantitative sample design.Natural horizontal stratification of the Rapel Reservoir (Central Chile) is produced mainly by suspended solids. The spatial heterogeneity conditions of the reservoir for the Spring 86-Summer 87 period were determined by qualitative analysis and image processing of the MSS Landsat, bands 1 and 3. The space-time variations of the different observed strata obtained with multitemporal image analysis.A random stratified sample design (r.s.s.d) was developed, based on the digital counts statistical analysis. Strata population size as well as the average, variance and sampling size of the digital counts were obtained by the r.s.s.d method.Stratification determined by analysis of satellite images were later correlated with ground data. Though the stratification of the reservoir is constant over time, the shape and size of the strata varys.

Cost-effective sampling of (137)Cs-derived net soil redistribution: part 2 - estimating the spatial mean change over time.

PubMed

Chappell, A; Li, Y; Yu, H Q; Zhang, Y Z; Li, X Y

2015-06-01

The caesium-137 ((137)Cs) technique for estimating net, time-integrated soil redistribution by the processes of wind, water and tillage is increasingly being used with repeated sampling to form a baseline to evaluate change over small (years to decades) timeframes. This interest stems from knowledge that since the 1950s soil redistribution has responded dynamically to different phases of land use change and management. Currently, there is no standard approach to detect change in (137)Cs-derived net soil redistribution and thereby identify the driving forces responsible for change. We outline recent advances in space-time sampling in the soil monitoring literature which provide a rigorous statistical and pragmatic approach to estimating the change over time in the spatial mean of environmental properties. We apply the space-time sampling framework, estimate the minimum detectable change of net soil redistribution and consider the information content and cost implications of different sampling designs for a study area in the Chinese Loess Plateau. Three phases (1954-1996, 1954-2012 and 1996-2012) of net soil erosion were detectable and attributed to well-documented historical change in land use and management practices in the study area and across the region. We recommend that the design for space-time sampling is considered carefully alongside cost-effective use of the spatial mean to detect and correctly attribute cause of change over time particularly across spatial scales of variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül

2015-01-01

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

Network-scale spatial and temporal variation in Chinook salmon (Oncorhynchus tshawytscha) redd distributions: patterns inferred from spatially continuous replicate surveys

Treesearch

Daniel J. Isaak; Russell F. Thurow

2006-01-01

Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...

Comparing three sampling techniques for estimating fine woody down dead biomass

Treesearch

Robert E. Keane; Kathy Gray

2013-01-01

Designing woody fuel sampling methods that quickly, accurately and efficiently assess biomass at relevant spatial scales requires extensive knowledge of each sampling method's strengths, weaknesses and tradeoffs. In this study, we compared various modifications of three common sampling methods (planar intercept, fixed-area microplot and photoload) for estimating...

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

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

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

Taking a statistical approach

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

Wild, M.; Rouhani, S.

1995-02-01

A typical site investigation entails extensive sampling and monitoring. In the past, sampling plans have been designed on purely ad hoc bases, leading to significant expenditures and, in some cases, collection of redundant information. In many instances, sampling costs exceed the true worth of the collected data. The US Environmental Protection Agency (EPA) therefore has advocated the use of geostatistics to provide a logical framework for sampling and analysis of environmental data. Geostatistical methodology uses statistical techniques for the spatial analysis of a variety of earth-related data. The use of geostatistics was developed by the mining industry to estimate oremore » concentrations. The same procedure is effective in quantifying environmental contaminants in soils for risk assessments. Unlike classical statistical techniques, geostatistics offers procedures to incorporate the underlying spatial structure of the investigated field. Sample points spaced close together tend to be more similar than samples spaced further apart. This can guide sampling strategies and determine complex contaminant distributions. Geostatistic techniques can be used to evaluate site conditions on the basis of regular, irregular, random and even spatially biased samples. In most environmental investigations, it is desirable to concentrate sampling in areas of known or suspected contamination. The rigorous mathematical procedures of geostatistics allow for accurate estimates at unsampled locations, potentially reducing sampling requirements. The use of geostatistics serves as a decision-aiding and planning tool and can significantly reduce short-term site assessment costs, long-term sampling and monitoring needs, as well as lead to more accurate and realistic remedial design criteria.« less

A New Stratified Sampling Procedure which Decreases Error Estimation of Varroa Mite Number on Sticky Boards.

PubMed

Kretzschmar, A; Durand, E; Maisonnasse, A; Vallon, J; Le Conte, Y

2015-06-01

A new procedure of stratified sampling is proposed in order to establish an accurate estimation of Varroa destructor populations on sticky bottom boards of the hive. It is based on the spatial sampling theory that recommends using regular grid stratification in the case of spatially structured process. The distribution of varroa mites on sticky board being observed as spatially structured, we designed a sampling scheme based on a regular grid with circles centered on each grid element. This new procedure is then compared with a former method using partially random sampling. Relative error improvements are exposed on the basis of a large sample of simulated sticky boards (n=20,000) which provides a complete range of spatial structures, from a random structure to a highly frame driven structure. The improvement of varroa mite number estimation is then measured by the percentage of counts with an error greater than a given level. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Dynamic Positron Emission Tomography [PET] in Man Using Small Bismuth Germanate Crystals

DOE R&D Accomplishments Database

Derenzo, S. E.; Budinger, T. F.; Huesman, R. H.; Cahoon, J. L.

1982-04-01

Primary considerations for the design of positron emission tomographs for medical studies in humans are the need for high imaging sensitivity, whole organ coverage, good spatial resolution, high maximum data rates, adequate spatial sampling with minimum mechanical motion, shielding against out of plane activity, pulse height discrimination against scattered photons, and timing discrimination against accidental coincidences. We discuss the choice of detectors, sampling motion, shielding, and electronics to meet these objectives.

PtyNAMi: ptychographic nano-analytical microscope at PETRA III: interferometrically tracking positions for 3D x-ray scanning microscopy using a ball-lens retroreflector

NASA Astrophysics Data System (ADS)

Schroer, Christian G.; Seyrich, Martin; Kahnt, Maik; Botta, Stephan; Döhrmann, Ralph; Falkenberg, Gerald; Garrevoet, Jan; Lyubomirskiy, Mikhail; Scholz, Maria; Schropp, Andreas; Wittwer, Felix

2017-09-01

In recent years, ptychography has revolutionized x-ray microscopy in that it is able to overcome the diffraction limit of x-ray optics, pushing the spatial resolution limit down to a few nanometers. However, due to the weak interaction of x rays with matter, the detection of small features inside a sample requires a high coherent fluence on the sample, a high degree of mechanical stability, and a low background signal from the x-ray microscope. The x-ray scanning microscope PtyNAMi at PETRA III is designed for high-spatial-resolution 3D imaging with high sensitivity. The design concept is presented with a special focus on real-time metrology of the sample position during tomographic scanning microscopy.

Linear chirped slope profile for spatial calibration in slope measuring deflectometry

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

Siewert, F., E-mail: frank.siewert@helmholtz-berlin.de; Zeschke, T.; Arnold, T.

2016-05-15

Slope measuring deflectometry is commonly used by the X-ray optics community to measure the long-spatial-wavelength surface figure error of optical components dedicated to guide and focus X-rays under grazing incidence condition at synchrotron and free electron laser beamlines. The best performing instruments of this kind are capable of absolute accuracy on the level of 30-50 nrad. However, the exact bandwidth of the measurements, determined at the higher spatial frequencies by the instrument’s spatial resolution, or more generally by the instrument’s modulation transfer function (MTF) is hard to determine. An MTF calibration method based on application of a test surface withmore » a one-dimensional (1D) chirped height profile of constant amplitude was suggested in the past. In this work, we propose a new approach to designing the test surfaces with a 2D-chirped topography, specially optimized for MTF characterization of slope measuring instruments. The design of the developed MTF test samples based on the proposed linear chirped slope profiles (LCSPs) is free of the major drawback of the 1D chirped height profiles, where in the slope domain, the amplitude strongly increases with the local spatial frequency of the profile. We provide the details of fabrication of the LCSP samples. The results of first application of the developed test samples to measure the spatial resolution of the BESSY-NOM at different experimental arrangements are also presented and discussed.« less

Performance of some biotic indices in the real variable world: a case study at different spatial scales in North-Western Mediterranean Sea.

PubMed

Tataranni, Mariella; Lardicci, Claudio

2010-01-01

The aim of this study was to analyse the variability of four different benthic biotic indices (AMBI, BENTIX, H', M-AMBI) in two marine coastal areas of the North-Western Mediterranean Sea. In each coastal area, 36 replicates were randomly selected according to a hierarchical sampling design, which allowed estimating the variance components of the indices associated with four different spatial scales (ranging from metres to kilometres). All the analyses were performed at two different sampling periods in order to evaluate if the observed trends were consistent over the time. The variance components of the four indices revealed complex trends and different patterns in the two sampling periods. These results highlighted that independently from the employed index, a rigorous and appropriate sampling design taking into account different scales should always be used in order to avoid erroneous classifications and to develop effective monitoring programs.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Optical design and simulation of a new coherence beamline at NSLS-II

NASA Astrophysics Data System (ADS)

Williams, Garth J.; Chubar, Oleg; Berman, Lonny; Chu, Yong S.; Robinson, Ian K.

2017-08-01

We will discuss the optical design for a proposed beamline at NSLS-II, a late-third generation storage ring source, designed to exploit the spatial coherence of the X-rays to extract high-resolution spatial information from ordered and disordered materials through Coherent Diffractive Imaging, executed in the Bragg- and forward-scattering geometries. This technique offers a powerful tool to image sub-10 nm spatial features and, within ordered materials, sub-Angstrom mapping of deformation fields. Driven by the opportunity to apply CDI to a wide range of samples, with sizes ranging from sub-micron to tens-of-microns, two optical designs have been proposed and simulated under a wide variety of optical configurations using the software package Synchrotron Radiation Workshop. The designs, their goals, and the results of the simulation, including NSLS-II ring and undulator source parameters, of the beamline performance as a function of its variable optical components is described.

Where do the Field Plots Belong? A Multiple-Constraint Sampling Design for the BigFoot Project

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Cohen, W. B.; Kirschbaum, A. A.; Gower, S. T.

2002-12-01

A key component of a MODIS validation project is effective characterization of biophysical measures on the ground. Fine-grain ecological field measurements must be placed strategically to capture variability at the scale of the MODIS imagery. Here we describe the BigFoot project's revised sampling scheme, designed to simultaneously meet three important goals: capture landscape variability, avoid spatial autocorrelation between field plots, and minimize time and expense of field sampling. A stochastic process places plots in clumped constellations to reduce field sampling costs, while minimizing spatial autocorrelation. This stochastic process is repeated, creating several hundred realizations of plot constellations. Each constellation is scored and ranked according to its ability to match landscape variability in several Landsat-based spectral indices, and its ability to minimize field sampling costs. We show how this approach has recently been used to place sample plots at the BigFoot project's two newest study areas, one in a desert system and one in a tundra system. We also contrast this sampling approach to that already used at the four prior BigFoot project sites.

Validating long-term satellite-derived disturbance products: the case of burned areas

NASA Astrophysics Data System (ADS)

Boschetti, L.; Roy, D. P.

2015-12-01

The potential research, policy and management applications of satellite products place a high priority on providing statements about their accuracy. A number of NASA, ESA and EU funded global and continental burned area products have been developed using coarse spatial resolution satellite data, and have the potential to become part of a long-term fire Climate Data Record. These products have usually been validated by comparison with reference burned area maps derived by visual interpretation of Landsat or similar spatial resolution data selected on an ad hoc basis. More optimally, a design-based validation method should be adopted that is characterized by the selection of reference data via a probability sampling that can subsequently be used to compute accuracy metrics, taking into account the sampling probability. Design based techniques have been used for annual land cover and land cover change product validation, but have not been widely used for burned area products, or for the validation of global products that are highly variable in time and space (e.g. snow, floods or other non-permanent phenomena). This has been due to the challenge of designing an appropriate sampling strategy, and to the cost of collecting independent reference data. We propose a tri-dimensional sampling grid that allows for probability sampling of Landsat data in time and in space. To sample the globe in the spatial domain with non-overlapping sampling units, the Thiessen Scene Area (TSA) tessellation of the Landsat WRS path/rows is used. The TSA grid is then combined with the 16-day Landsat acquisition calendar to provide tri-dimensonal elements (voxels). This allows the implementation of a sampling design where not only the location but also the time interval of the reference data is explicitly drawn by probability sampling. The proposed sampling design is a stratified random sampling, with two-level stratification of the voxels based on biomes and fire activity (Figure 1). The novel validation approach, used for the validation of the MODIS and forthcoming VIIRS global burned area products, is a general one, and could be used for the validation of other global products that are highly variable in space and time and is required to assess the accuracy of climate records. The approach is demonstrated using a 1 year dataset of MODIS fire products.

Electromagnetic Design of a Magnetically Coupled Spatial Power Combiner

NASA Astrophysics Data System (ADS)

Bulcha, B. T.; Cataldo, G.; Stevenson, T. R.; U-Yen, K.; Moseley, S. H.; Wollack, E. J.

2018-04-01

The design of a two-dimensional spatial beam-combining network employing a parallel-plate superconducting waveguide filled with a monocrystalline silicon dielectric substrate is presented. This component uses arrays of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multimode waveguide region. These attributes enable the structure's use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. If unterminated, reflections within a finite-sized spatial beam combiner can potentially lead to spurious couplings between elements. A planar meta-material electromagnetic absorber is implemented to control this response within the device. This broadband termination absorbs greater than 0.99 of the power over the 1.7:1 operational band at angles ranging from normal to near-parallel incidence. The design approach, simulations and applications of the spatial power combiner and meta-material termination structure are presented.

Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

NASA Astrophysics Data System (ADS)

Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

2013-06-01

Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that the effect of uncertainties associated with the geostatistical parameters on the spatial prediction might be significantly alleviated (by up to 80% of the prior uncertainty in K and by 90% of the prior uncertainty in H) by sampling evenly distributed measurements with a spatial measurement density of more than 1 observation per 60 m × 60 m grid block. In addition, exploration of the interaction of objective functions indicates that the ability of head measurements to reduce the uncertainty associated with the correlation scale is comparable to the effect of hydraulic conductivity measurements.

A comparison of five sampling techniques to estimate surface fuel loading in montane forests

Treesearch

Pamela G. Sikkink; Robert E. Keane

2008-01-01

Designing a fuel-sampling program that accurately and efficiently assesses fuel load at relevant spatial scales requires knowledge of each sample method's strengths and weaknesses.We obtained loading values for six fuel components using five fuel load sampling techniques at five locations in western Montana, USA. The techniques included fixed-area plots, planar...

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

Spatial distribution of Munida intermedia and M. sarsi (crustacea: Anomura) on the Galician continental shelf (NW Spain): Application of geostatistical analysis

NASA Astrophysics Data System (ADS)

Freire, J.; González-Gurriarán, E.; Olaso, I.

1992-12-01

Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.

The relationship between observational scale and explained variance in benthic communities

PubMed Central

Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.

2018-01-01

This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746

Spatial analysis of the distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) and losses in maize crop productivity using geostatistics.

PubMed

Farias, Paulo R S; Barbosa, José C; Busoli, Antonio C; Overal, William L; Miranda, Vicente S; Ribeiro, Susane M

2008-01-01

The fall armyworm, Spodoptera frugiperda (J.E. Smith), is one of the chief pests of maize in the Americas. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling methods, determining actual and potential crop losses, and adopting precise agricultural techniques. In São Paulo state, Brazil, a maize field was sampled at weekly intervals, from germination through harvest, for caterpillar densities, using quadrates. In each of 200 quadrates, 10 plants were sampled per week. Harvest weights were obtained in the field for each quadrate, and ear diameters and lengths were also sampled (15 ears per quadrate) and used to estimate potential productivity of the quadrate. Geostatistical analyses of caterpillar densities showed greatest ranges for small caterpillars when semivariograms were adjusted for a spherical model that showed greatest fit. As the caterpillars developed in the field, their spatial distribution became increasingly random, as shown by a model adjusted to a straight line, indicating a lack of spatial dependence among samples. Harvest weight and ear length followed the spherical model, indicating the existence of spatial variability of the production parameters in the maize field. Geostatistics shows promise for the application of precise methods in the integrated control of pests.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

PubMed

Jia, Jie; Barnard, Kenneth J; Hirakawa, Keigo

2016-04-01

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.

The surface water register: an empirically improved sample frame for monitoring the rivers and streams of Kansas

EPA Science Inventory

State-wide monitoring based on probability survey designs requires a spatially explicit representation of all streams and rivers of interest within a state, i.e., a sample frame. The sample frame should be the best available map representation of the resource. Many stream progr...

A priori evaluation of two-stage cluster sampling for accuracy assessment of large-area land-cover maps

USGS Publications Warehouse

Wickham, J.D.; Stehman, S.V.; Smith, J.H.; Wade, T.G.; Yang, L.

2004-01-01

Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, within-cluster correlation may reduce the precision of the accuracy estimates. The detailed population information to quantify a priori the effect of within-cluster correlation on precision is typically unavailable. Consequently, a convenient, practical approach to evaluate the likely performance of a two-stage cluster sample is needed. We describe such an a priori evaluation protocol focusing on the spatial distribution of the sample by land-cover class across different cluster sizes and costs of different sampling options, including options not imposing clustering. This protocol also assesses the two-stage design's adequacy for estimating the precision of accuracy estimates for rare land-cover classes. We illustrate the approach using two large-area, regional accuracy assessments from the National Land-Cover Data (NLCD), and describe how the a priorievaluation was used as a decision-making tool when implementing the NLCD design.

Estimating the encounter rate variance in distance sampling

USGS Publications Warehouse

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

The effect of childhood trauma on spatial cognition in adults: a possible role of sex.

PubMed

Syal, Supriya; Ipser, Jonathan; Phillips, Nicole; Thomas, Kevin G F; van der Honk, Jack; Stein, Dan J

2014-06-01

Although animal evidence indicates that early life trauma results in pervasive hippocampal deficits underlying spatial and cognitive impairment, visuo-spatial data from adult humans with early childhood adversity are lacking. We administered 4 tests of visuo-spatial ability from the Cambridge Neuorpsychological Test Automated Battery (CANTAB) to adults with a history of childhood trauma (measured by the Childhood Trauma Questionnaire) and a matched sample of healthy controls (trauma/control = 27/28). We observed a significant effect of trauma history on spatial/pattern learning. These effects could not be accounted for by adverse adult experiences, and were sex-specific, with prior adversity improving performance in men but worsening performance in women, relative to controls. Limitations include the small sample size and reliance of our study design on a retrospective, self report measure. Our results suggest that early adversity can lead to specific and pervasive deficits in adult cognitive function.

Multidimensional System Analysis of Electro-Optic Sensors with Sampled Deterministic Output.

DTIC Science & Technology

1987-12-18

System descriptions of scanning and staring electro - optic sensors with sampled output are developed as follows. Functions representing image...to complete the system descriptions. The results should be useful for designing electro - optic sensor systems and correcting data for instrumental...effects and other experimental conditions. Keywords include: Electro - optic system analysis, Scanning sensors, Staring sensors, Spatial sampling, and Temporal sampling.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

PubMed

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions

PubMed Central

Hahn, Beth A.; Dreitz, Victoria J.; George, T. Luke

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer’s sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer’s sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales. PMID:29065128

Advanced Instrumentation for Positron Emission Tomography [PET

DOE R&D Accomplishments Database

Derenzo, S. E.; Budinger, T. F.

1985-04-01

This paper summarizes the physical processes and medical science goals that underlay modern instrumentation design for Positron Emission Tomography. The paper discusses design factors such as detector material, crystalphototube coupling, shielding geometry, sampling motion, electronics design, time-of-flight, and the interrelationships with quantitative accuracy, spatial resolution, temporal resolution, maximum data rates, and cost.

Spatial-temporal models for improved county-level annual estimates

Treesearch

Francis Roesch

2009-01-01

The consumers of data derived from extensive forest inventories often seek annual estimates at a finer spatial scale than that which the inventory was designed to provide. This paper discusses a few model-based and model-assisted estimators to consider for county level attributes that can be applied when the sample would otherwise be inadequate for producing low-...

The Effect of Origami-Based Instruction on Spatial Visualization, Geometry Achievement, and Geometric Reasoning

ERIC Educational Resources Information Center

Arici, Sevil; Aslan-Tutak, Fatma

2015-01-01

This research study examined the effect of origami-based geometry instruction on spatial visualization, geometry achievement, and geometric reasoning of tenth-grade students in Turkey. The sample ("n" = 184) was chosen from a tenth-grade population of a public high school in Turkey. It was a quasi-experimental pretest/posttest design. A…

Training in Mental Rotation and Spatial Visualization and Its Impact on Orthographic Drawing Performance

ERIC Educational Resources Information Center

Samsudin, Khairulanuar; Rafi, Ahmad; Hanif, Abd Samad

2011-01-01

This paper reports the findings from an experimental study based on the pretest posttest research design that studied mental rotation (MR) and spatial visualization (SV) training outcomes and their impact on orthographic drawing performance. The sample of the study comprised 98 secondary school students (36 girls, 62 boys, Mage = 15.5 years, age…

DESIGNING MONITORING AND ASSESSMENT STRATEGIES TO INCLUDE NEARSHORE ECOSYSTEMS OF THE GREAT LAKES

EPA Science Inventory

An expectation for monitoring and assessment of very large aquatic systems is that we can develop a strategy that recognizes and reports on ecologically-important subareas using spatially-stratified, probabilistic sampling designs. Ongoing efforts monitor the main-body, offshore ...

Design and analysis for detection monitoring of forest health

Treesearch

F. A. Roesch

1995-01-01

An analysis procedure is proposed for the sample design of the Forest Health Monitoring Program (FHM) in the United States. The procedure is intended to provide increased sensitivity to localized but potentially important changes in forest health by explicitly accounting for the spatial relationships between plots in the FHM design. After a series of median sweeps...

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

PubMed Central

Broekhuis, Femke; Gopalaswamy, Arjun M.

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

PubMed

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

Determination of geostatistically representative sampling locations in Porsuk Dam Reservoir (Turkey)

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yenilmez, F.; Duzgun, S.

2013-12-01

Several factors such as wind action, bathymetry and shape of a lake/reservoir, inflows, outflows, point and diffuse pollution sources result in spatial and temporal variations in water quality of lakes and reservoirs. The guides by the United Nations Environment Programme and the World Health Organization to design and implement water quality monitoring programs suggest that even a single monitoring station near the center or at the deepest part of a lake will be sufficient to observe long-term trends if there is good horizontal mixing. In stratified water bodies, several samples can be required. According to the guide of sampling and analysis under the Turkish Water Pollution Control Regulation, a minimum of five sampling locations should be employed to characterize the water quality in a reservoir or a lake. The European Union Water Framework Directive (2000/60/EC) states to select a sufficient number of monitoring sites to assess the magnitude and impact of point and diffuse sources and hydromorphological pressures in designing a monitoring program. Although existing regulations and guidelines include frameworks for the determination of sampling locations in surface waters, most of them do not specify a procedure in establishment of monitoring aims with representative sampling locations in lakes and reservoirs. In this study, geostatistical tools are used to determine the representative sampling locations in the Porsuk Dam Reservoir (PDR). Kernel density estimation and kriging were used in combination to select the representative sampling locations. Dissolved oxygen and specific conductivity were measured at 81 points. Sixteen of them were used for validation. In selection of the representative sampling locations, care was given to keep similar spatial structure in distributions of measured parameters. A procedure was proposed for that purpose. Results indicated that spatial structure was lost under 30 sampling points. This was as a result of varying water quality in the reservoir due to inflows, point and diffuse inputs, and reservoir hydromorphology. Moreover, hot spots were determined based on kriging and standard error maps. Locations of minimum number of sampling points that represent the actual spatial structure of DO distribution in the Porsuk Dam Reservoir

Detection of forest stand-level spatial structure in ectomycorrhizal fungal communities

Treesearch

Erik A. Lilleskov; Thomas D. Bruns; Thomas R. Horton; D. Lee Taylor; Paul Grogan

2004-01-01

Ectomycorrhizal fungal (EMF) communities are highly diverse at the stand level. To begin to understand what might lead to such diversity, and to improve sampling designs, we investigated the spatial structure of these communities. We used EMF community data from a number of studies carried out in seven mature and one recently fire-initiated forest stand. We applied...

Determination of Spatially Resolved Tablet Density and Hardness Using Near-Infrared Chemical Imaging (NIR-CI).

PubMed

Talwar, Sameer; Roopwani, Rahul; Anderson, Carl A; Buckner, Ira S; Drennen, James K

2017-08-01

Near-infrared chemical imaging (NIR-CI) combines spectroscopy with digital imaging, enabling spatially resolved analysis and characterization of pharmaceutical samples. Hardness and relative density are critical quality attributes (CQA) that affect tablet performance. Intra-sample density or hardness variability can reveal deficiencies in formulation design or the tableting process. This study was designed to develop NIR-CI methods to predict spatially resolved tablet density and hardness. The method was implemented using a two-step procedure. First, NIR-CI was used to develop a relative density/solid fraction (SF) prediction method for pure microcrystalline cellulose (MCC) compacts only. A partial least squares (PLS) model for predicting SF was generated by regressing the spectra of certain representative pixels selected from each image against the compact SF. Pixel selection was accomplished with a threshold based on the Euclidean distance from the median tablet spectrum. Second, micro-indentation was performed on the calibration compacts to obtain hardness values. A univariate model was developed by relating the empirical hardness values to the NIR-CI predicted SF at the micro-indented pixel locations: this model generated spatially resolved hardness predictions for the entire tablet surface.

Igniting Creativity and Planning for Your Gifted Students.

ERIC Educational Resources Information Center

Russell, Don W., Ed.

The collection of instructional plans is designed to offer samples of strategies and ideas to teachers involved with gifted students. Approximately 30 plans are presented for the following areas (sample subtopics in science (atomic fusion), social studies (mores and folkways), mathematics (spatial relations), health and physiology, philosophy, and…

Enabling low-noise null-point scanning thermal microscopy by the optimization of scanning thermal microscope probe through a rigorous theory of quantitative measurement.

PubMed

Hwang, Gwangseok; Chung, Jaehun; Kwon, Ohmyoung

2014-11-01

The application of conventional scanning thermal microscopy (SThM) is severely limited by three major problems: (i) distortion of the measured signal due to heat transfer through the air, (ii) the unknown and variable value of the tip-sample thermal contact resistance, and (iii) perturbation of the sample temperature due to the heat flux through the tip-sample thermal contact. Recently, we proposed null-point scanning thermal microscopy (NP SThM) as a way of overcoming these problems in principle by tracking the thermal equilibrium between the end of the SThM tip and the sample surface. However, in order to obtain high spatial resolution, which is the primary motivation for SThM, NP SThM requires an extremely sensitive SThM probe that can trace the vanishingly small heat flux through the tip-sample nano-thermal contact. Herein, we derive a relation between the spatial resolution and the design parameters of a SThM probe, optimize the thermal and electrical design, and develop a batch-fabrication process. We also quantitatively demonstrate significantly improved sensitivity, lower measurement noise, and higher spatial resolution of the fabricated SThM probes. By utilizing the exceptional performance of these fabricated probes, we show that NP SThM can be used to obtain a quantitative temperature profile with nanoscale resolution independent of the changing tip-sample thermal contact resistance and without perturbation of the sample temperature or distortion due to the heat transfer through the air.

Spatial distribution, sampling precision and survey design optimisation with non-normal variables: The case of anchovy (Engraulis encrasicolus) recruitment in Spanish Mediterranean waters

NASA Astrophysics Data System (ADS)

Tugores, M. Pilar; Iglesias, Magdalena; Oñate, Dolores; Miquel, Joan

2016-02-01

In the Mediterranean Sea, the European anchovy (Engraulis encrasicolus) displays a key role in ecological and economical terms. Ensuring stock sustainability requires the provision of crucial information, such as species spatial distribution or unbiased abundance and precision estimates, so that management strategies can be defined (e.g. fishing quotas, temporal closure areas or marine protected areas MPA). Furthermore, the estimation of the precision of global abundance at different sampling intensities can be used for survey design optimisation. Geostatistics provide a priori unbiased estimations of the spatial structure, global abundance and precision for autocorrelated data. However, their application to non-Gaussian data introduces difficulties in the analysis in conjunction with low robustness or unbiasedness. The present study applied intrinsic geostatistics in two dimensions in order to (i) analyse the spatial distribution of anchovy in Spanish Western Mediterranean waters during the species' recruitment season, (ii) produce distribution maps, (iii) estimate global abundance and its precision, (iv) analyse the effect of changing the sampling intensity on the precision of global abundance estimates and, (v) evaluate the effects of several methodological options on the robustness of all the analysed parameters. The results suggested that while the spatial structure was usually non-robust to the tested methodological options when working with the original dataset, it became more robust for the transformed datasets (especially for the log-backtransformed dataset). The global abundance was always highly robust and the global precision was highly or moderately robust to most of the methodological options, except for data transformation.

Simulations inform design of regional occupancy-based monitoring for a sparsely distributed, territorial species

Treesearch

Quresh S. Latif; Martha M. Ellis; Victoria A. Saab; Kim Mellen-McLean

2017-01-01

Sparsely distributed species attract conservation concern, but insufficient information on population trends challenges conservation and funding prioritization. Occupancy-based monitoring is attractive for these species, but appropriate sampling design and inference depend on particulars of the study system. We employed spatially explicit simulations to identify...

The New Bedford Harbor Superfund site long-term monitoring program (1993-2009).

PubMed

Nelson, William G; Bergen, Barbara J

2012-12-01

New Bedford Harbor (NBH), located in southeastern Massachusetts, was designated as a marine Superfund site in 1983 due to sediment contamination by polychlorinated biphenyls (PCBs). Based on risks to human health and the environment, the first two phases of the site cleanup involved dredging PCB-contaminated sediments from the harbor. Therefore, a long-term monitoring program (LTM) was developed to measure spatial and temporal chemical and biological changes in sediment, water, and biota to assess the effects and effectiveness of the remedial activities. A systematic, probabilistic sampling design was used to select sediment sampling stations. This unbiased design allowed the three segments of the harbor to be compared spatially and temporally to quantify changes resulting from dredging the contaminated sediments. Sediment was collected at each station, and chemical (e.g., PCBs and metals), physical (e.g., grain size), and biological (e.g., benthic community) measurements were conducted on all samples. This paper describes the overall NBH-LTM approach and the results from the five rounds of sample collections. There is a decreasing spatial gradient in sediment PCB concentrations from the northern boundary (upper harbor) to the southern boundary (outer harbor) of the site. Along this same transect, there is an increase in biological condition (e.g., benthic community diversity). Temporally, the contaminant and biological gradients have been maintained since the 1993 baseline collection; however, since the onset of full-scale remediation, PCB concentrations have decreased throughout the site, and one of the benthic community indices has shown significant improvement in the lower and outer harbor areas.

Space and time aliasing structure is monthly mean polar-orbiting satellite data

NASA Technical Reports Server (NTRS)

Zeng, Lixin; Levy, Gad

1995-01-01

Monthly mean wind fields from the European Remote Sensing Satellite (ERS1) scatterometer are presented. A banded structure which resembles the satellite subtrack is clearly and consistently apparent in the isotachs as well as the u and v components of the routinely produced fields. The structure also appears in the means of data from other polar-orbiting satellites and instruments. An experiment is designed to trace the cause of the banded structure. The European Centre for Medium-Range Weather Forecast (ECMWF) gridded surface wind analyses are used as a control set. These analyses are also sampled with the ERS1 temporal-spatial samplig pattern to form a simulated scatterometer wind set. Both sets are used to create monthly averages. The banded structures appear in the monthly mean simulated data but do not appear in the control set. It is concluded that the source of the banded structure lies in the spatial and temporal sampling of the polar-orbiting satellite which results in undersampling. The problem involves multiple timescales and space scales, oversampling and under-sampling in space, aliasing in the time and space domains, and preferentially sampled variability. It is shown that commonly used spatial smoothers (or filters), while producing visually pleasing results, also significantly bias the true mean. A three-dimensional spatial-temporal interpolator is designed and used to determine the mean field. It is found to produce satisfactory monthly means from both simulated and real ERS1 data. The implications to climate studies involving polar-orbiting satellite data are discussed.

Cost-effective sampling of ¹³⁷Cs-derived net soil redistribution: part 1--estimating the spatial mean across scales of variation.

PubMed

Li, Y; Chappell, A; Nyamdavaa, B; Yu, H; Davaasuren, D; Zoljargal, K

2015-03-01

The (137)Cs technique for estimating net time-integrated soil redistribution is valuable for understanding the factors controlling soil redistribution by all processes. The literature on this technique is dominated by studies of individual fields and describes its typically time-consuming nature. We contend that the community making these studies has inappropriately assumed that many (137)Cs measurements are required and hence estimates of net soil redistribution can only be made at the field scale. Here, we support future studies of (137)Cs-derived net soil redistribution to apply their often limited resources across scales of variation (field, catchment, region etc.) without compromising the quality of the estimates at any scale. We describe a hybrid, design-based and model-based, stratified random sampling design with composites to estimate the sampling variance and a cost model for fieldwork and laboratory measurements. Geostatistical mapping of net (1954-2012) soil redistribution as a case study on the Chinese Loess Plateau is compared with estimates for several other sampling designs popular in the literature. We demonstrate the cost-effectiveness of the hybrid design for spatial estimation of net soil redistribution. To demonstrate the limitations of current sampling approaches to cut across scales of variation, we extrapolate our estimate of net soil redistribution across the region, show that for the same resources, estimates from many fields could have been provided and would elucidate the cause of differences within and between regional estimates. We recommend that future studies evaluate carefully the sampling design to consider the opportunity to investigate (137)Cs-derived net soil redistribution across scales of variation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Escherichia coli sampling reliability at a frequently closed Chicago beach: monitoring and management implications

USGS Publications Warehouse

Whitman, Richard L.; Nevers, Meredith B.

2004-01-01

Monitoring beaches for recreational water quality is becoming more common, but few sampling designs or policy approaches have evaluated the efficacy of monitoring programs. The authors intensively sampled water for E. coli (N=1770) at 63rd Street Beach, Chicago for 6 months in 2000 in order to (1) characterize spatial-temporal trends, (2) determine between and within transect variation, and (3) estimate sample size requirements and determine sampling reliability.E. coli counts were highly variable within and between sampling sites but spatially and diurnally autocorrelated. Variation in counts decreased with water depth and time of day. Required number of samples was high for 70% precision around the critical closure level (i.e., 6 within or 24 between transect replicates). Since spatial replication may be cost prohibitive, composite sampling is an alternative once sources of error have been well defined. The results suggest that beach monitoring programs may be requiring too few samples to fulfill management objectives desired. As the recreational water quality national database is developed, it is important that sampling strategies are empirically derived from a thorough understanding of the sources of variation and the reliability of collected data. Greater monitoring efficacy will yield better policy decisions, risk assessments, programmatic goals, and future usefulness of the information.

A Numerical Climate Observing Network Design Study

NASA Technical Reports Server (NTRS)

Stammer, Detlef

2003-01-01

This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: "Optimal observations for variational data assimilation".

Spatial Variability of the Topsoil Organic Carbon in the Moso Bamboo Forests of Southern China in Association with Soil Properties

PubMed Central

Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao

2015-01-01

Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production. PMID:25789615

A phoswich detector design for improved spatial sampling in PET

NASA Astrophysics Data System (ADS)

Thiessen, Jonathan D.; Koschan, Merry A.; Melcher, Charles L.; Meng, Fang; Schellenberg, Graham; Goertzen, Andrew L.

2018-02-01

Block detector designs, utilizing a pixelated scintillator array coupled to a photosensor array in a light-sharing design, are commonly used for positron emission tomography (PET) imaging applications. In practice, the spatial sampling of these designs is limited by the crystal pitch, which must be large enough for individual crystals to be resolved in the detector flood image. Replacing the conventional 2D scintillator array with an array of phoswich elements, each consisting of an optically coupled side-by-side scintillator pair, may improve spatial sampling in one direction of the array without requiring resolving smaller crystal elements. To test the feasibility of this design, a 4 × 4 phoswich array was constructed, with each phoswich element consisting of two optically coupled, 3 . 17 × 1 . 58 × 10mm3 LSO crystals co-doped with cerium and calcium. The amount of calcium doping was varied to create a 'fast' LSO crystal with decay time of 32.9 ns and a 'slow' LSO crystal with decay time of 41.2 ns. Using a Hamamatsu R8900U-00-C12 position-sensitive photomultiplier tube (PS-PMT) and a CAEN V1720 250 MS/s waveform digitizer, we were able to show effective discrimination of the fast and slow LSO crystals in the phoswich array. Although a side-by-side phoswich array is feasible, reflections at the crystal boundary due to a mismatch between the refractive index of the optical adhesive (n = 1 . 5) and LSO (n = 1 . 82) caused it to behave optically as an 8 × 4 array rather than a 4 × 4 array. Direct coupling of each phoswich element to individual photodetector elements may be necessary with the current phoswich array design. Alternatively, in order to implement this phoswich design with a conventional light sharing PET block detector, a high refractive index optical adhesive is necessary to closely match the refractive index of LSO.

Precision of systematic and random sampling in clustered populations: habitat patches and aggregating organisms.

PubMed

McGarvey, Richard; Burch, Paul; Matthews, Janet M

2016-01-01

Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν₈ and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν₂ and ν₃) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with a second differently generated set of spatial point populations, ν₈ and ν(W) again being the best performers in the longer-range autocorrelated populations. However, no systematic variance estimators tested were free from bias. On balance, systematic designs bring more narrow confidence intervals in clustered populations, while random designs permit unbiased estimates of (often wider) confidence interval. The search continues for better estimators of sampling variance for the systematic survey mean.

Detection of forest stand-level spatial structure in ectomycorrhizal fungal communities.

PubMed

Lilleskov, Erik A; Bruns, Thomas D; Horton, Thomas R; Taylor, D; Grogan, Paul

2004-08-01

Ectomycorrhizal fungal (EMF) communities are highly diverse at the stand level. To begin to understand what might lead to such diversity, and to improve sampling designs, we investigated the spatial structure of these communities. We used EMF community data from a number of studies carried out in seven mature and one recently fire-initiated forest stand. We applied various measures of spatial pattern to characterize distributions at EMF community and species levels: Mantel tests, Mantel correlograms, variance/mean and standardized variograms. Mantel tests indicated that in four of eight sites community similarity decreased with distance, whereas Mantel correlograms also found spatial autocorrelation in those four plus two additional sites. In all but one of these sites elevated similarity was evident only at relatively small spatial scales (< 2.6 m), whereas one exhibited a larger scale pattern ( approximately 25 m). Evenness of biomass distribution among cores varied widely among taxa. Standardized variograms indicated that most of the dominant taxa showed patchiness at a scale of less than 3 m, with a range from 0 to < or =17 m. These results have implications for both sampling scale and intensity to achieve maximum efficiency of community sampling. In the systems we examined, cores should be at least 3 m apart to achieve the greatest sampling efficiency for stand-level community analysis. In some cases even this spacing may result in reduced sampling efficiency arising from patterns of spatial autocorrelation. Interpretation of the causes and significance of these patterns requires information on the genetic identity of individuals in the communities.

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

USGS Publications Warehouse

Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

2018-01-01

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

Practical guidance on characterizing availability in resource selection functions under a use-availability design

USGS Publications Warehouse

Northrup, Joseph M.; Hooten, Mevin B.; Anderson, Charles R.; Wittemyer, George

2013-01-01

Habitat selection is a fundamental aspect of animal ecology, the understanding of which is critical to management and conservation. Global positioning system data from animals allow fine-scale assessments of habitat selection and typically are analyzed in a use-availability framework, whereby animal locations are contrasted with random locations (the availability sample). Although most use-availability methods are in fact spatial point process models, they often are fit using logistic regression. This framework offers numerous methodological challenges, for which the literature provides little guidance. Specifically, the size and spatial extent of the availability sample influences coefficient estimates potentially causing interpretational bias. We examined the influence of availability on statistical inference through simulations and analysis of serially correlated mule deer GPS data. Bias in estimates arose from incorrectly assessing and sampling the spatial extent of availability. Spatial autocorrelation in covariates, which is common for landscape characteristics, exacerbated the error in availability sampling leading to increased bias. These results have strong implications for habitat selection analyses using GPS data, which are increasingly prevalent in the literature. We recommend researchers assess the sensitivity of their results to their availability sample and, where bias is likely, take care with interpretations and use cross validation to assess robustness.

Validation of the MODIS Collection 6 MCD64 Global Burned Area Product

NASA Astrophysics Data System (ADS)

Boschetti, L.; Roy, D. P.; Giglio, L.; Stehman, S. V.; Humber, M. L.; Sathyachandran, S. K.; Zubkova, M.; Melchiorre, A.; Huang, H.; Huo, L. Z.

2017-12-01

The research, policy and management applications of satellite products place a high priority on rigorously assessing their accuracy. A number of NASA, ESA and EU funded global and continental burned area products have been developed using coarse spatial resolution satellite data, and have the potential to become part of a long-term fire Essential Climate Variable. These products have usually been validated by comparison with reference burned area maps derived by visual interpretation of Landsat or similar spatial resolution data selected on an ad hoc basis. More optimally, a design-based validation method should be adopted, characterized by the selection of reference data via probability sampling. Design based techniques have been used for annual land cover and land cover change product validation, but have not been widely used for burned area products, or for other products that are highly variable in time and space (e.g. snow, floods, other non-permanent phenomena). This has been due to the challenge of designing an appropriate sampling strategy, and to the cost and limited availability of independent reference data. This paper describes the validation procedure adopted for the latest Collection 6 version of the MODIS Global Burned Area product (MCD64, Giglio et al, 2009). We used a tri-dimensional sampling grid that allows for probability sampling of Landsat data in time and in space (Boschetti et al, 2016). To sample the globe in the spatial domain with non-overlapping sampling units, the Thiessen Scene Area (TSA) tessellation of the Landsat WRS path/rows is used. The TSA grid is then combined with the 16-day Landsat acquisition calendar to provide tri-dimensonal elements (voxels). This allows the implementation of a sampling design where not only the location but also the time interval of the reference data is explicitly drawn through stratified random sampling. The novel sampling approach was used for the selection of a reference dataset consisting of 700 Landsat 8 image pairs, interpreted according to the CEOS Burned Area Validation Protocol (Boschetti et al., 2009). Standard quantitative burned area product accuracy measures that are important for different types of fire users (Boschetti et al, 2016, Roy and Boschetti, 2009, Boschetti et al, 2004) are computed to characterize the accuracy of the MCD64 product.

Shaped saturation with inherent radiofrequency-power-efficient trajectory design in parallel transmission.

PubMed

Schneider, Rainer; Haueisen, Jens; Pfeuffer, Josef

2014-10-01

A target-pattern-driven (TD) trajectory design is introduced in combination with parallel transmit (pTX) radiofrequency (RF) pulses to provide localized suppression of unwanted signals. The design incorporates target-pattern and B1+ information to adjust denser sampling and coverage in k-space regions where the main pattern information lies. Based on this approach, two-dimensional RF spiral saturation pulses sensitive to RF power limits were applied in vivo for the first time. The TD method was compared with two state-of-the-art spiral design methods. Simulations at different spatial fidelities, acceleration factors and anatomical regions were carried out for an eight-channel pTX 3 Tesla (T) coil. Human in vivo experiments were performed on a two-channel pTX 3T scanner saturating shaped patterns in the brain, heart, and thoracic spine. Using the TD trajectory, RF pulse power can be substantially reduced by up to 34% compared with other trajectory designs with the same spatial accuracy. Local and global specific absorption rates are decreased in most cases. The TD trajectory design uses available a priori information to enhance RF power efficiency and spatial response of the RF pulses. Shaped saturation pulses show improved spatial accuracy and saturation performance. Thus, RF pulses can be designed more efficiently and can be further accelerated. Copyright © 2013 Wiley Periodicals, Inc.

Evaluating sampling designs by computer simulation: A case study with the Missouri bladderpod

USGS Publications Warehouse

Morrison, L.W.; Smith, D.R.; Young, C.; Nichols, D.W.

2008-01-01

To effectively manage rare populations, accurate monitoring data are critical. Yet many monitoring programs are initiated without careful consideration of whether chosen sampling designs will provide accurate estimates of population parameters. Obtaining accurate estimates is especially difficult when natural variability is high, or limited budgets determine that only a small fraction of the population can be sampled. The Missouri bladderpod, Lesquerella filiformis Rollins, is a federally threatened winter annual that has an aggregated distribution pattern and exhibits dramatic interannual population fluctuations. Using the simulation program SAMPLE, we evaluated five candidate sampling designs appropriate for rare populations, based on 4 years of field data: (1) simple random sampling, (2) adaptive simple random sampling, (3) grid-based systematic sampling, (4) adaptive grid-based systematic sampling, and (5) GIS-based adaptive sampling. We compared the designs based on the precision of density estimates for fixed sample size, cost, and distance traveled. Sampling fraction and cost were the most important factors determining precision of density estimates, and relative design performance changed across the range of sampling fractions. Adaptive designs did not provide uniformly more precise estimates than conventional designs, in part because the spatial distribution of L. filiformis was relatively widespread within the study site. Adaptive designs tended to perform better as sampling fraction increased and when sampling costs, particularly distance traveled, were taken into account. The rate that units occupied by L. filiformis were encountered was higher for adaptive than for conventional designs. Overall, grid-based systematic designs were more efficient and practically implemented than the others. ?? 2008 The Society of Population Ecology and Springer.

NEON terrestrial field observations: designing continental scale, standardized sampling

Treesearch

R. H. Kao; C.M. Gibson; R. E. Gallery; C. L. Meier; D. T. Barnett; K. M. Docherty; K. K. Blevins; P. D. Travers; E. Azuaje; Y. P. Springer; K. M. Thibault; V. J. McKenzie; M. Keller; L. F. Alves; E. L. S. Hinckley; J. Parnell; D. Schimel

2012-01-01

Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use,...

Low photon-count tip-tilt sensor

NASA Astrophysics Data System (ADS)

Saathof, Rudolf; Schitter, Georg

2016-07-01

Due to the low photon-count of dark areas of the universe, signal strength of tip-tilt sensor is low, limiting sky-coverage of reliable tip-tilt measurements. This paper presents the low photon-count tip-tilt (LPC-TT) sensor, which potentially achieves improved signal strength. Its optical design spatially samples and integrates the scene. This increases the probability that several individual sources coincide on a detector segment. Laboratory experiments show feasibility of spatial sampling and integration and the ability to measure tilt angles. By simulation an improvement of the SNR of 10 dB compared to conventional tip-tilt sensors is shown.

High-resolution room-temperature sample scanning superconducting quantum interference device microscope configurable for geological and biomagnetic applications

NASA Astrophysics Data System (ADS)

Fong, L. E.; Holzer, J. R.; McBride, K. K.; Lima, E. A.; Baudenbacher, F.; Radparvar, M.

2005-05-01

We have developed a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with submillimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensors are mounted on the tip of a sapphire and thermally anchored to the helium reservoir. A 25μm sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows us to adjust the sample-to-sensor spacing from the top of the Dewar. We achieved a sensor-to-sample spacing of 100μm, which could be maintained for periods of up to four weeks. Different SQUID sensor designs are necessary to achieve the best combination of spatial resolution and field sensitivity for a given source configuration. For imaging thin sections of geological samples, we used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80μm, and achieved a field sensitivity of 1.5pT/Hz1/2 and a magnetic moment sensitivity of 5.4×10-18Am2/Hz1/2 at a sensor-to-sample spacing of 100μm in the white noise region for frequencies above 100Hz. Imaging action currents in cardiac tissue requires a higher field sensitivity, which can only be achieved by compromising spatial resolution. We developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250μm to 1mm, and achieved sensitivities of 480-180fT /Hz1/2 in the white noise region for frequencies above 100Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

PubMed

Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

2017-01-01

Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial autocorrelation in an SDM context and, by taking account of random effects, produce outputs that can better elucidate the role of covariates in predicting species occurrence. Given that it is often unclear what the drivers are behind data clumping in an empirical occurrence dataset, or indeed how geographically restricted these data are, spatially-explicit Bayesian SDMs may be the better choice when modelling the spatial distribution of target species.

A statistical evaluation of non-ergodic variogram estimators

USGS Publications Warehouse

Curriero, F.C.; Hohn, M.E.; Liebhold, A.M.; Lele, S.R.

2002-01-01

Geostatistics is a set of statistical techniques that is increasingly used to characterize spatial dependence in spatially referenced ecological data. A common feature of geostatistics is predicting values at unsampled locations from nearby samples using the kriging algorithm. Modeling spatial dependence in sampled data is necessary before kriging and is usually accomplished with the variogram and its traditional estimator. Other types of estimators, known as non-ergodic estimators, have been used in ecological applications. Non-ergodic estimators were originally suggested as a method of choice when sampled data are preferentially located and exhibit a skewed frequency distribution. Preferentially located samples can occur, for example, when areas with high values are sampled more intensely than other areas. In earlier studies the visual appearance of variograms from traditional and non-ergodic estimators were compared. Here we evaluate the estimators' relative performance in prediction. We also show algebraically that a non-ergodic version of the variogram is equivalent to the traditional variogram estimator. Simulations, designed to investigate the effects of data skewness and preferential sampling on variogram estimation and kriging, showed the traditional variogram estimator outperforms the non-ergodic estimators under these conditions. We also analyzed data on carabid beetle abundance, which exhibited large-scale spatial variability (trend) and a skewed frequency distribution. Detrending data followed by robust estimation of the residual variogram is demonstrated to be a successful alternative to the non-ergodic approach.

Using Remote Sensing to Determine the Spatial Scales of Estuaries

NASA Astrophysics Data System (ADS)

Davis, C. O.; Tufillaro, N.; Nahorniak, J.

2016-02-01

One challenge facing Earth system science is to understand and quantify the complexity of rivers, estuaries, and coastal zone regions. Earlier studies using data from airborne hyperspectral imagers (Bissett et al., 2004, Davis et al., 2007) demonstrated from a very limited data set that the spatial scales of the coastal ocean could be resolved with spatial sampling of 100 m Ground Sample Distance (GSD) or better. To develop a much larger data set (Aurin et al., 2013) used MODIS 250 m data for a wide range of coastal regions. Their conclusion was that farther offshore 500 m GSD was adequate to resolve large river plume features while nearshore regions (a few kilometers from the coast) needed higher spatial resolution data not available from MODIS. Building on our airborne experience, the Hyperspectral Imager for the Coastal Ocean (HICO, Lucke et al., 2011) was designed to provide hyperspectral data for the coastal ocean at 100 m GSD. HICO operated on the International Space Station for 5 years and collected over 10,000 scenes of the coastal ocean and other regions around the world. Here we analyze HICO data from an example set of major river delta regions to assess the spatial scales of variability in those systems. In one system, the San Francisco Bay and Delta, we also analyze Landsat 8 OLI data at 30 m and 15 m to validate the 100 m GSD sampling scale for the Bay and assess spatial sampling needed as you move up river.

APPLICATION OF THE ELECTROMAGNETIC BOREHOLE FLOWMETER

EPA Science Inventory

Spatial variability of saturated zone hydraulic properties has important implications with regard to sampling wells for water quality parameters, use of conventional methods to estimate transmissivity, and remedial system design. Characterization of subsurface heterogeneity requ...

Computerized stratified random site-selection approaches for design of a ground-water-quality sampling network

USGS Publications Warehouse

Scott, J.C.

1990-01-01

Computer software was written to randomly select sites for a ground-water-quality sampling network. The software uses digital cartographic techniques and subroutines from a proprietary geographic information system. The report presents the approaches, computer software, and sample applications. It is often desirable to collect ground-water-quality samples from various areas in a study region that have different values of a spatial characteristic, such as land-use or hydrogeologic setting. A stratified network can be used for testing hypotheses about relations between spatial characteristics and water quality, or for calculating statistical descriptions of water-quality data that account for variations that correspond to the spatial characteristic. In the software described, a study region is subdivided into areal subsets that have a common spatial characteristic to stratify the population into several categories from which sampling sites are selected. Different numbers of sites may be selected from each category of areal subsets. A population of potential sampling sites may be defined by either specifying a fixed population of existing sites, or by preparing an equally spaced population of potential sites. In either case, each site is identified with a single category, depending on the value of the spatial characteristic of the areal subset in which the site is located. Sites are selected from one category at a time. One of two approaches may be used to select sites. Sites may be selected randomly, or the areal subsets in the category can be grouped into cells and sites selected randomly from each cell.

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

Future VIIRS enhancements for the integrated polar-orbiting environmental satellite system

NASA Astrophysics Data System (ADS)

Puschell, Jeffery J.; Silny, John; Cook, Lacy; Kim, Eugene

2010-08-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) is the next-generation imaging spectroradiometer for the future operational polar-orbiting environmental satellite system. A successful Flight Unit 1 has been delivered and integrated onto the NPP spacecraft. The flexible VIIRS architecture can be adapted and enhanced to respond to a wide range of requirements and to incorporate new technology as it becomes available. This paper reports on recent design studies to evaluate building a MW-VLWIR dispersive hyperspectral module with active cooling into the existing VIIRS architecture. Performance of a two-grating VIIRS hyperspectral module was studied across a broad trade space defined primarily by spatial sampling, spectral range, spectral sampling interval, along-track field of view and integration time. The hyperspectral module studied here provides contiguous coverage across 3.9 - 15.5 μm with a spectral sampling interval of 10 nm or better, thereby extending VIIRS spectral range to the shortwave side of the 15.5 μm CO2 band and encompassing the 6.7 μm H2O band. Spatial sampling occurs at VIIRS I-band (~0.4 km at nadir) spatial resolution with aggregation to M-band (~0.8 km) and larger pixel sizes to improve sensitivity. Radiometric sensitivity (NEdT) at a spatial resolution of ~4 km is ~0.1 K or better for a 250 K scene across a wavelength range of 4.5 μm to 15.5 μm. The large number of high spectral and spatial resolution FOVs in this instrument improves chances for retrievals of information on the physical state and composition of the atmosphere all the way to the surface in cloudy regions relative to current systems. Spectral aggregation of spatial resolution measurements to MODIS and VIIRS multispectral bands would continue legacy measurements with better sensitivity in nearly all bands. Additional work is needed to optimize spatial sampling, spectral range and spectral sampling approaches for the hyperspectral module and to further refine this powerful imager concept.

Assessment of Potential Location of High Arsenic Contamination Using Fuzzy Overlay and Spatial Anisotropy Approach in Iron Mine Surrounding Area

PubMed Central

Wirojanagud, Wanpen; Srisatit, Thares

2014-01-01

Fuzzy overlay approach on three raster maps including land slope, soil type, and distance to stream can be used to identify the most potential locations of high arsenic contamination in soils. Verification of high arsenic contamination was made by collection samples and analysis of arsenic content and interpolation surface by spatial anisotropic method. A total of 51 soil samples were collected at the potential contaminated location clarified by fuzzy overlay approach. At each location, soil samples were taken at the depth of 0.00-1.00 m from the surface ground level. Interpolation surface of the analysed arsenic content using spatial anisotropic would verify the potential arsenic contamination location obtained from fuzzy overlay outputs. Both outputs of the spatial surface anisotropic and the fuzzy overlay mapping were significantly spatially conformed. Three contaminated areas with arsenic concentrations of 7.19 ± 2.86, 6.60 ± 3.04, and 4.90 ± 2.67 mg/kg exceeded the arsenic content of 3.9 mg/kg, the maximum concentration level (MCL) for agricultural soils as designated by Office of National Environment Board of Thailand. It is concluded that fuzzy overlay mapping could be employed for identification of potential contamination area with the verification by surface anisotropic approach including intensive sampling and analysis of the substances of interest. PMID:25110751

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

PubMed

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes ≪200, currently available data are prone to large uncertainties.

Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain

PubMed Central

2014-01-01

Background Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. Methods We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. Results During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Conclusions Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling. PMID:24735818

Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain.

PubMed

Shmool, Jessie Lc; Michanowicz, Drew R; Cambal, Leah; Tunno, Brett; Howell, Jeffery; Gillooly, Sara; Roper, Courtney; Tripathy, Sheila; Chubb, Lauren G; Eisl, Holger M; Gorczynski, John E; Holguin, Fernando E; Shields, Kyra Naumoff; Clougherty, Jane E

2014-04-16

Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling.

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

PubMed

Steenweg, Robin; Hebblewhite, Mark; Whittington, Jesse; Lukacs, Paul; McKelvey, Kevin

2018-01-01

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship. © 2017 by the Ecological Society of America.

Visuo-spatial performance in autism: a meta-analysis.

PubMed

Muth, Anne; Hönekopp, Johannes; Falter, Christine M

2014-12-01

Visuo-spatial skills are believed to be enhanced in autism spectrum disorders (ASDs). This meta-analysis tests the current state of evidence for Figure Disembedding, Block Design, Mental Rotation and Navon tasks in ASD and neurotypicals. Block Design (d = 0.32) and Figure Disembedding (d = 0.26) showed superior performance for ASD with large heterogeneity that is unaccounted for. No clear differences were found for Mental Rotation. ASD samples showed a stronger local processing preference for Navon tasks (d = 0.35); less clear evidence for performance differences of a similar magnitude emerged. We discuss the meta-analysis results together with other findings relating to visuo-spatial processing and three cognitive theories of ASD: Weak Central Coherence, Enhanced Perceptual Functioning and Extreme Male Brain theory.

Assessing accuracy of point fire intervals across landscapes with simulation modelling

Treesearch

Russell A. Parsons; Emily K. Heyerdahl; Robert E. Keane; Brigitte Dorner; Joseph Fall

2007-01-01

We assessed accuracy in point fire intervals using a simulation model that sampled four spatially explicit simulated fire histories. These histories varied in fire frequency and size and were simulated on a flat landscape with two forest types (dry versus mesic). We used three sampling designs (random, systematic grids, and stratified). We assessed the sensitivity of...

Composition, biomass and structure of mangroves within the Zambezi River Delta

Treesearch

Carl C. Trettin; Christina E. Stringer; Stan Zarnoch

2015-01-01

We used a stratified random sampling design to inventory the mangrove vegetation within the Zambezi River Delta, Mozambique, to provide a basis for estimating biomass pools. We used canopy height, derived from remote sensing data, to stratify the inventory area, and then applied a spatial decision support system to objectively allocate sample plots among five...

Statistical strategy for inventorying and monitoring the ecosystem resources of the Mexican States of Jalisco and Colima at multiple scales and resolution levels

Treesearch

H. T. Schreuder; M. S. Williams; C. Aguirre-Bravo; P. L. Patterson

2003-01-01

The sampling strategy is presented for the initial phase of the natural resources pilot project in the Mexican States of Jalisco and Colima. The sampling design used is ground-based cluster sampling with poststratification based on Landsat Thematic Mapper imagery. The data collected will serve as a basis for additional data collection, mapping, and spatial modeling...

Sampling design and required sample size for evaluating contamination levels of 137Cs in Japanese fir needles in a mixed deciduous forest stand in Fukushima, Japan.

PubMed

Oba, Yurika; Yamada, Toshihiro

2017-05-01

We estimated the sample size (the number of samples) required to evaluate the concentration of radiocesium ( 137 Cs) in Japanese fir (Abies firma Sieb. & Zucc.), 5 years after the outbreak of the Fukushima Daiichi Nuclear Power Plant accident. We investigated the spatial structure of the contamination levels in this species growing in a mixed deciduous broadleaf and evergreen coniferous forest stand. We sampled 40 saplings with a tree height of 150 cm-250 cm in a Fukushima forest community. The results showed that: (1) there was no correlation between the 137 Cs concentration in needles and soil, and (2) the difference in the spatial distribution pattern of 137 Cs concentration between needles and soil suggest that the contribution of root uptake to 137 Cs in new needles of this species may be minor in the 5 years after the radionuclides were released into the atmosphere. The concentration of 137 Cs in needles showed a strong positive spatial autocorrelation in the distance class from 0 to 2.5 m, suggesting that the statistical analysis of data should consider spatial autocorrelation in the case of an assessment of the radioactive contamination of forest trees. According to our sample size analysis, a sample size of seven trees was required to determine the mean contamination level within an error in the means of no more than 10%. This required sample size may be feasible for most sites. Copyright © 2017 Elsevier Ltd. All rights reserved.

An overview of the Columbia Habitat Monitoring Program's (CHaMP) spatial-temporal design framework

EPA Science Inventory

We briefly review the concept of a master sample applied to stream networks in which a randomized set of stream sites is selected across a broad region to serve as a list of sites from which a subset of sites is selected to achieve multiple objectives of specific designs. The Col...

Improved lossless intra coding for H.264/MPEG-4 AVC.

PubMed

Lee, Yung-Lyul; Han, Ki-Hun; Sullivan, Gary J

2006-09-01

A new lossless intra coding method based on sample-by-sample differential pulse code modulation (DPCM) is presented as an enhancement of the H.264/MPEG-4 AVC standard. The H.264/AVC design includes a multidirectional spatial prediction method to reduce spatial redundancy by using neighboring samples as a prediction for the samples in a block of data to be encoded. In the new lossless intra coding method, the spatial prediction is performed based on samplewise DPCM instead of in the block-based manner used in the current H.264/AVC standard, while the block structure is retained for the residual difference entropy coding process. We show that the new method, based on samplewise DPCM, does not have a major complexity penalty, despite its apparent pipeline dependencies. Experiments show that the new lossless intra coding method reduces the bit rate by approximately 12% in comparison with the lossless intra coding method previously included in the H.264/AVC standard. As a result, the new method is currently being adopted into the H.264/AVC standard in a new enhancement project.

Intelligent Sampling of Hazardous Particle Populations in Resource-Constrained Environments

NASA Astrophysics Data System (ADS)

McCollough, J. P.; Quinn, J. M.; Starks, M. J.; Johnston, W. R.

2017-10-01

Sampling of anomaly-causing space environment drivers is necessary for both real-time operations and satellite design efforts, and optimizing measurement sampling helps minimize resource demands. Relating these measurements to spacecraft anomalies requires the ability to resolve spatial and temporal variability in the energetic charged particle hazard of interest. Here we describe a method for sampling particle fluxes informed by magnetospheric phenomenology so that, along a given trajectory, the variations from both temporal dynamics and spatial structure are adequately captured while minimizing oversampling. We describe the coordinates, sampling method, and specific regions and parameters employed. We compare resulting sampling cadences with data from spacecraft spanning the regions of interest during a geomagnetically active period, showing that the algorithm retains the gross features necessary to characterize environmental impacts on space systems in diverse orbital regimes while greatly reducing the amount of sampling required. This enables sufficient environmental specification within a resource-constrained context, such as limited telemetry bandwidth, processing requirements, and timeliness.

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.

Spatial versus Day-To-Day Within-Lake Variability in Tropical Floodplain Lake CH4 Emissions – Developing Optimized Approaches to Representative Flux Measurements

PubMed Central

Peixoto, Roberta B.; Machado-Silva, Fausto; Marotta, Humberto; Enrich-Prast, Alex; Bastviken, David

2015-01-01

Inland waters (lakes, rivers and reservoirs) are now understood to contribute large amounts of methane (CH4) to the atmosphere. However, fluxes are poorly constrained and there is a need for improved knowledge on spatiotemporal variability and on ways of optimizing sampling efforts to yield representative emission estimates for different types of aquatic ecosystems. Low-latitude floodplain lakes and wetlands are among the most high-emitting environments, and here we provide a detailed investigation of spatial and day-to-day variability in a shallow floodplain lake in the Pantanal in Brazil over a five-day period. CH4 flux was dominated by frequent and ubiquitous ebullition. A strong but predictable spatial variability (decreasing flux with increasing distance to the shore or to littoral vegetation) was found, and this pattern can be addressed by sampling along transects from the shore to the center. Although no distinct day-to-day variability were found, a significant increase in flux was identified from measurement day 1 to measurement day 5, which was likely attributable to a simultaneous increase in temperature. Our study demonstrates that representative emission assessments requires consideration of spatial variability, but also that spatial variability patterns are predictable for lakes of this type and may therefore be addressed through limited sampling efforts if designed properly (e.g., fewer chambers may be used if organized along transects). Such optimized assessments of spatial variability are beneficial by allowing more of the available sampling resources to focus on assessing temporal variability, thereby improving overall flux assessments. PMID:25860229

Measurement of bite force variables related to human discrimination of left-right hardness differences of silicone rubber samples placed between the incisors.

PubMed

Dan, Haruka; Azuma, Teruaki; Hayakawa, Fumiyo; Kohyama, Kaoru

2005-05-01

This study was designed to examine human subjects' ability to discriminate between spatially different bite pressures. We measured actual bite pressure distribution when subjects simultaneously bit two silicone rubber samples with different hardnesses using their right and left incisors. They were instructed to compare the hardness of these two rubber samples and indicate which was harder (right or left). The correct-answer rates were statistically significant at P < 0.05 for all pairs of different right and left silicone rubber hardnesses. Simultaneous bite measurements using a multiple-point sheet sensor demonstrated that the bite force, active pressure and maximum pressure point were greater for the harder silicone rubber sample. The difference between the left and right was statistically significant (P < 0.05) for all pairs with different silicone rubber hardnesses. We demonstrated for the first time that subjects could perceive and discriminate between spatially different bite pressures during a single bite with incisors. Differences of the bite force, pressure and the maximum pressure point between the right and left silicone samples should be sensory cues for spatial hardness discrimination.

Estuarine water quality in parks of the Northeast Coastal and Barrier Network: Development and early implementation of vital signs estuarine nutrient-enrichment monitoring, 2003-06

USGS Publications Warehouse

Kopp, Blaine S.; Nielsen, Martha; Glisic, Dejan; Neckles, Hilary A.

2009-01-01

This report documents results of pilot tests of a protocol for monitoring estuarine nutrient enrichment for the Vital Signs Monitoring Program of the National Park Service Northeast Coastal and Barrier Network. Data collected from four parks during protocol development in 2003-06 are presented: Gateway National Recreation Area, Colonial National Historic Park, Fire Island National Seashore, and Assateague Island National Seashore. The monitoring approach incorporates several spatial and temporal designs to address questions at a hierarchy of scales. Indicators of estuarine response to nutrient enrichment were sampled using a probability design within park estuaries during a late-summer index period. Monitoring variables consisted of dissolved-oxygen concentration, chlorophyll a concentration, water temperature, salinity, attenuation of downwelling photosynthetically available radiation (PAR), and turbidity. The statistical sampling design allowed the condition of unsampled locations to be inferred from the distribution of data from a set of randomly positioned "probability" stations. A subset of sampling stations was sampled repeatedly during the index period, and stations were not rerandomized in subsequent years. These "trend stations" allowed us to examine temporal variability within the index period, and to improve the sensitivity of the monitoring protocol to detecting change through time. Additionally, one index site in each park was equipped for continuous monitoring throughout the index period. Thus, the protocol includes elements of probabilistic and targeted spatial sampling, and the temporal intensity ranges from snapshot assessments to continuous monitoring.

Objective Assessment and Design Improvement of a Staring, Sparse Transducer Array by the Spatial Crosstalk Matrix for 3D Photoacoustic Tomography

PubMed Central

Kosik, Ivan; Raess, Avery

2015-01-01

Accurate reconstruction of 3D photoacoustic (PA) images requires detection of photoacoustic signals from many angles. Several groups have adopted staring ultrasound arrays, but assessment of array performance has been limited. We previously reported on a method to calibrate a 3D PA tomography (PAT) staring array system and analyze system performance using singular value decomposition (SVD). The developed SVD metric, however, was impractical for large system matrices, which are typical of 3D PAT problems. The present study consisted of two main objectives. The first objective aimed to introduce the crosstalk matrix concept to the field of PAT for system design. Figures-of-merit utilized in this study were root mean square error, peak signal-to-noise ratio, mean absolute error, and a three dimensional structural similarity index, which were derived between the normalized spatial crosstalk matrix and the identity matrix. The applicability of this approach for 3D PAT was validated by observing the response of the figures-of-merit in relation to well-understood PAT sampling characteristics (i.e. spatial and temporal sampling rate). The second objective aimed to utilize the figures-of-merit to characterize and improve the performance of a near-spherical staring array design. Transducer arrangement, array radius, and array angular coverage were the design parameters examined. We observed that the performance of a 129-element staring transducer array for 3D PAT could be improved by selection of optimal values of the design parameters. The results suggested that this formulation could be used to objectively characterize 3D PAT system performance and would enable the development of efficient strategies for system design optimization. PMID:25875177

Canceling the momentum in a phase-shifting algorithm to eliminate spatially uniform errors.

PubMed

Hibino, Kenichi; Kim, Yangjin

2016-08-10

In phase-shifting interferometry, phase modulation nonlinearity causes both spatially uniform and nonuniform errors in the measured phase. Conventional linear-detuning error-compensating algorithms only eliminate the spatially variable error component. The uniform error is proportional to the inertial momentum of the data-sampling weight of a phase-shifting algorithm. This paper proposes a design approach to cancel the momentum by using characteristic polynomials in the Z-transform space and shows that an arbitrary M-frame algorithm can be modified to a new (M+2)-frame algorithm that acquires new symmetry to eliminate the uniform error.

So Close to a Deal: Spatial-Distance Cues Influence Economic Decision-Making in a Social Context.

PubMed

Fatfouta, Ramzi; Schulreich, Stefan; Meshi, Dar; Heekeren, Hauke

2015-01-01

Social distance (i.e., the degree of closeness to another person) affects the way humans perceive and respond to fairness during financial negotiations. Feeling close to someone enhances the acceptance of monetary offers. Here, we explored whether this effect also extends to the spatial domain. Specifically, using an iterated version of the Ultimatum Game in a within-subject design, we investigated whether different visual spatial distance-cues result in different rates of acceptance of otherwise identical monetary offers. Study 1 found that participants accepted significantly more offers when they were cued with spatial closeness than when they were cued with spatial distance. Study 2 replicated this effect using identical procedures but different spatial-distance cues in an independent sample. Importantly, our results could not be explained by feelings of social closeness. Our results demonstrate that mere perceptions of spatial closeness produce analogous-but independent-effects to those of social closeness.

APPLICATION OF THE ELECTROMAGNETIC BOREHOLE FLOWMETER (EPA/600/R-98/058)

EPA Science Inventory

Spatial variability of saturated zone hydraulic properties has important implications with regard to sampling wells for water quality parameters, use of conventional methods to estimate transmissivity, and remedial system design. Characterization of subsurface heterogeneity requi...

APPLICATION OF THE ELECTROMAGNETIC BOREHOLE FLOWMETER (EPA/600/SR-98/058)

EPA Science Inventory

Spatial variability of saturated zone hydraulic properties has important implications with regard to sampling wells for water quality parameters, use of conventional methods to estimate transmissivity, and remedial system design. Characterization of subsurface heterogeneity requi...

HEAVY METALS STRUCTURE BENTHIC COMUNITIES IN COLORADO MOUNTAIN STREAMS

EPA Science Inventory

The development of field sampling designs that employ multiple reference and polluted sites has been proposed as an alternative to the traditional upstream vs. downstream approach used in most biomonitoring studies. Spatially extensive monitoring programs can characterize ecologi...

Application of spatially gridded temperature and land cover data sets for urban heat island analysis

USGS Publications Warehouse

Gallo, Kevin; Xian, George Z.

2014-01-01

Two gridded data sets that included (1) daily mean temperatures from 2006 through 2011 and (2) satellite-derived impervious surface area, were combined for a spatial analysis of the urban heat-island effect within the Dallas-Ft. Worth Texas region. The primary advantage of using these combined datasets included the capability to designate each 1 × 1 km grid cell of available temperature data as urban or rural based on the level of impervious surface area within the grid cell. Generally, the observed differences in urban and rural temperature increased as the impervious surface area thresholds used to define an urban grid cell were increased. This result, however, was also dependent on the size of the sample area included in the analysis. As the spatial extent of the sample area increased and included a greater number of rural defined grid cells, the observed urban and rural differences in temperature also increased. A cursory comparison of the spatially gridded temperature observations with observations from climate stations suggest that the number and location of stations included in an urban heat island analysis requires consideration to assure representative samples of each (urban and rural) environment are included in the analysis.

Trading Space for Time in Design Storm Estimation Using Radar Data

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Berndt, C.

2017-12-01

Intensity-duration-frequency (IDF) curves are frequently used for the derivation of design storms. These curves are usually estimated from rain gauges and are valid for extreme rainfall at local observed points. Two common problems are involved. Regionalization of rainfall statistics for unobserved locations and the use of areal reduction factors (ARF) for the adjustment to larger catchments are required. Weather radar data are available with large spatial coverage and high resolution in space and could be used for a direct derivation of areal design storms for any location and catchment size. However, one problem with radar data is the relatively short observation period for the estimation of extreme events. This study deals with the estimation of area-intensity-duration-frequency (AIDF) curves and areal-reduction-factors (ARF) directly from weather radar data. The main objective is to answer the question if it is possible to trade space for time in the estimation of both characteristics to compensate for the short radar observation periods. In addition, a stratification of the temporal sample according to annual temperature indices is tried to distinguish "colder" and "warmer" climate years. This might eventually show a way for predicting future changes in AIDF curves and ARFs. First, radar data are adjusted with rainfall observations from the daily station network. Thereafter, AIDF curves and ARFs are calculated for different spatial and temporal sample sizes. The AIDF and ARFs are compared regarding their temporal and spatial variability considering also the temperature conditions. In order to reduce spatial variability a grouping of locations according to their climatological and physiographical characteristics is carried out. The data used for this study cover about 20 years of observations from the radar device located near Hanover in Northern Germany and 500 non-recording rain gauges as well as a set of 8 recording rain gauges for validation. AIDF curves and ARFS are analyzed for rainfall durations from 5 minutes to 24 hours and return periods from 1 year to 30 years. It is hypothesized, that the spatial variability of AIDF and ARF characteristics decreases with increasing sample size, grouping and normalization and is finally comparable to temporal variability.

A spatial multi-objective optimization model for sustainable urban wastewater system layout planning.

PubMed

Dong, X; Zeng, S; Chen, J

2012-01-01

Design of a sustainable city has changed the traditional centralized urban wastewater system towards a decentralized or clustering one. Note that there is considerable spatial variability of the factors that affect urban drainage performance including urban catchment characteristics. The potential options are numerous for planning the layout of an urban wastewater system, which are associated with different costs and local environmental impacts. There is thus a need to develop an approach to find the optimal spatial layout for collecting, treating, reusing and discharging the municipal wastewater of a city. In this study, a spatial multi-objective optimization model, called Urban wastewateR system Layout model (URL), was developed. It is solved by a genetic algorithm embedding Monte Carlo sampling and a series of graph algorithms. This model was illustrated by a case study in a newly developing urban area in Beijing, China. Five optimized system layouts were recommended to the local municipality for further detailed design.

SAS procedures for designing and analyzing sample surveys

USGS Publications Warehouse

Stafford, Joshua D.; Reinecke, Kenneth J.; Kaminski, Richard M.

2003-01-01

Complex surveys often are necessary to estimate occurrence (or distribution), density, and abundance of plants and animals for purposes of re-search and conservation. Most scientists are familiar with simple random sampling, where sample units are selected from a population of interest (sampling frame) with equal probability. However, the goal of ecological surveys often is to make inferences about populations over large or complex spatial areas where organisms are not homogeneously distributed or sampling frames are in-convenient or impossible to construct. Candidate sampling strategies for such complex surveys include stratified,multistage, and adaptive sampling (Thompson 1992, Buckland 1994).

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Spatial capture–recapture with partial identity: An application to camera traps

USGS Publications Warehouse

Augustine, Ben C.; Royle, J. Andrew; Kelly, Marcella J.; Satter, Christopher B.; Alonso, Robert S.; Boydston, Erin E.; Crooks, Kevin R.

2018-01-01

Camera trapping surveys frequently capture individuals whose identity is only known from a single flank. The most widely used methods for incorporating these partial identity individuals into density analyses discard some of the partial identity capture histories, reducing precision, and, while not previously recognized, introducing bias. Here, we present the spatial partial identity model (SPIM), which uses the spatial location where partial identity samples are captured to probabilistically resolve their complete identities, allowing all partial identity samples to be used in the analysis. We show that the SPIM outperforms other analytical alternatives. We then apply the SPIM to an ocelot data set collected on a trapping array with double-camera stations and a bobcat data set collected on a trapping array with single-camera stations. The SPIM improves inference in both cases and, in the ocelot example, individual sex is determined from photographs used to further resolve partial identities—one of which is resolved to near certainty. The SPIM opens the door for the investigation of trapping designs that deviate from the standard two camera design, the combination of other data types between which identities cannot be deterministically linked, and can be extended to the problem of partial genotypes.

High spatial sampling light-guide snapshot spectrometer

PubMed Central

Wang, Ye; Pawlowski, Michal E.; Tkaczyk, Tomasz S.

2017-01-01

A prototype fiber-based imaging spectrometer was developed to provide snapshot hyperspectral imaging tuned for biomedical applications. The system is designed for imaging in the visible spectral range from 400 to 700 nm for compatibility with molecular imaging applications as well as satellite and remote sensing. An 81 × 96 pixel spatial sampling density is achieved by using a custom-made fiber-optic bundle. The design considerations and fabrication aspects of the fiber bundle and imaging spectrometer are described in detail. Through the custom fiber bundle, the image of a scene of interest is collected and divided into discrete spatial groups, with spaces generated in between groups for spectral dispersion. This reorganized image is scaled down by an image taper for compatibility with following optical elements, dispersed by a prism, and is finally acquired by a CCD camera. To obtain an (x, y, λ) datacube from the snapshot measurement, a spectral calibration algorithm is executed for reconstruction of the spatial–spectral signatures of the observed scene. System characterization of throughput, resolution, and crosstalk was performed. Preliminary results illustrating changes in oxygen-saturation in an occluded human finger are presented to demonstrate the system’s capabilities. PMID:29238115

Sub-micrometer resolution proximity X-ray microscope with digital image registration

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

Chkhalo, N. I.; Salashchenko, N. N.; Sherbakov, A. V., E-mail: SherbakovAV@ipm.sci-nnov.ru

A compact laboratory proximity soft X-ray microscope providing submicrometer spatial resolution and digital image registration is described. The microscope consists of a laser-plasma soft X-ray radiation source, a Schwarzschild objective to illuminate the test sample, and a two-coordinate detector for image registration. Radiation, which passes through the sample under study, generates an absorption image on the front surface of the detector. Optical ceramic YAG:Ce was used to convert the X-rays into visible light. An image was transferred from the scintillator to a charge-coupled device camera with a Mitutoyo Plan Apo series lens. The detector’s design allows the use of lensesmore » with numerical apertures of NA = 0.14, 0.28, and 0.55 without changing the dimensions and arrangement of the elements of the device. This design allows one to change the magnification, spatial resolution, and field of view of the X-ray microscope. A spatial resolution better than 0.7 μm and an energy conversion efficiency of the X-ray radiation with a wavelength of 13.5 nm into visible light collected by the detector of 7.2% were achieved with the largest aperture lens.« less

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Design of 2D time-varying vector fields.

PubMed

Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D; Zhang, Eugene

2012-10-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects.

SDSS-IV MaNGA IFS GALAXY SURVEY—SURVEY DESIGN, EXECUTION, AND INITIAL DATA QUALITY

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

Yan, Renbin; Zhang, Kai; Bundy, Kevin

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R  ∼ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how thesemore » science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R{sub e}) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5 R{sub e} (Primary sample), and one-third of the sample is covered to 2.5 R{sub e} (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r -band signal-to-noise ratio is ∼70 per 1.4 Å pixel for spectra stacked between 1 R{sub e} and 1.5 R{sub e}. Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.« less

SDSS-IV MaNGA IFS Galaxy Survey—Survey Design, Execution, and Initial Data Quality

NASA Astrophysics Data System (ADS)

Yan, Renbin; Bundy, Kevin; Law, David R.; Bershady, Matthew A.; Andrews, Brett; Cherinka, Brian; Diamond-Stanic, Aleksandar M.; Drory, Niv; MacDonald, Nicholas; Sánchez-Gallego, José R.; Thomas, Daniel; Wake, David A.; Weijmans, Anne-Marie; Westfall, Kyle B.; Zhang, Kai; Aragón-Salamanca, Alfonso; Belfiore, Francesco; Bizyaev, Dmitry; Blanc, Guillermo A.; Blanton, Michael R.; Brownstein, Joel; Cappellari, Michele; D'Souza, Richard; Emsellem, Eric; Fu, Hai; Gaulme, Patrick; Graham, Mark T.; Goddard, Daniel; Gunn, James E.; Harding, Paul; Jones, Amy; Kinemuchi, Karen; Li, Cheng; Li, Hongyu; Maiolino, Roberto; Mao, Shude; Maraston, Claudia; Masters, Karen; Merrifield, Michael R.; Oravetz, Daniel; Pan, Kaike; Parejko, John K.; Sanchez, Sebastian F.; Schlegel, David; Simmons, Audrey; Thanjavur, Karun; Tinker, Jeremy; Tremonti, Christy; van den Bosch, Remco; Zheng, Zheng

2016-12-01

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R ˜ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R e ) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5R e (Primary sample), and one-third of the sample is covered to 2.5R e (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r-band signal-to-noise ratio is ˜70 per 1.4 Å pixel for spectra stacked between 1R e and 1.5R e . Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

Quantitative Digital Autoradiography for Environmental Swipe Sample Prioritization: System design, Characterization, and Initial Measurements

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

McDonald, Benjamin S.; Zalavadia, Mital A.; Miller, Brian W.

Environmental sampling and sample analyses by the International Atomic Energy Agency’s (IAEA) Network of Analytical Laboratories (NWAL) is a critical technical tool used to detect facility misuse under a Comprehensive Safeguards Agreement and to verify the absence of undeclared nuclear material activities under an Additional Protocol. Currently all environmental swipe samples (ESS) are screened using gamma spectrometry and x-ray fluorescence to estimate the amount of U and/or Pu in the ESS, to guide further analysis, and to assist in the shipment of ESS to the NWAL. Quantitative Digital Autoradiography for Environmental Samples (QDARES) is being developed to complement existing techniquesmore » through the use of a portable, real-time, high-spatial-resolution camera called the Ionizing-radiation Quantum Imaging Detector (iQID). The iQID constructs a spatial map of radionuclides within a sample or surface in real-time as charged particles (betas) and photons (gamma/x-rays) are detected and localized on an event-by-event basis. Knowledge of the location and nature of radioactive hot spots on the ESS could provide information for subsequent laboratory analysis. As a nondestructive technique, QDARES does not compromise the ESS chain of custody or subsequent laboratory analysis. In this paper we will present the system design and construction, characterization measurements with calibration sources, and initial measurements of ESS.« less

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

Evaluation of process errors in bed load sampling using a Dune Model

USGS Publications Warehouse

Gomez, Basil; Troutman, Brent M.

1997-01-01

Reliable estimates of the streamwide bed load discharge obtained using sampling devices are dependent upon good at-a-point knowledge across the full width of the channel. Using field data and information derived from a model that describes the geometric features of a dune train in terms of a spatial process observed at a fixed point in time, we show that sampling errors decrease as the number of samples collected increases, and the number of traverses of the channel over which the samples are collected increases. It also is preferable that bed load sampling be conducted at a pace which allows a number of bed forms to pass through the sampling cross section. The situations we analyze and simulate pertain to moderate transport conditions in small rivers. In such circumstances, bed load sampling schemes typically should involve four or five traverses of a river, and the collection of 20–40 samples at a rate of five or six samples per hour. By ensuring that spatial and temporal variability in the transport process is accounted for, such a sampling design reduces both random and systematic errors and hence minimizes the total error involved in the sampling process.

Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes

NASA Astrophysics Data System (ADS)

Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian

2014-05-01

Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.

A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

Treesearch

Sean P. Healey; Paul L. Patterson; Sassan S. Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman

2012-01-01

Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform "shots," which have been shown to be strongly correlated with aboveground forest...

Graph-Based Semi-Supervised Hyperspectral Image Classification Using Spatial Information

NASA Astrophysics Data System (ADS)

Jamshidpour, N.; Homayouni, S.; Safari, A.

2017-09-01

Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

Under-sampling trajectory design for compressed sensing based DCE-MRI.

PubMed

Liu, Duan-duan; Liang, Dong; Zhang, Na; Liu, Xin; Zhang, Yuan-ting

2013-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) needs high temporal and spatial resolution to accurately estimate quantitative parameters and characterize tumor vasculature. Compressed Sensing (CS) has the potential to accomplish this mutual importance. However, the randomness in CS under-sampling trajectory designed using the traditional variable density (VD) scheme may translate to uncertainty in kinetic parameter estimation when high reduction factors are used. Therefore, accurate parameter estimation using VD scheme usually needs multiple adjustments on parameters of Probability Density Function (PDF), and multiple reconstructions even with fixed PDF, which is inapplicable for DCE-MRI. In this paper, an under-sampling trajectory design which is robust to the change on PDF parameters and randomness with fixed PDF is studied. The strategy is to adaptively segment k-space into low-and high frequency domain, and only apply VD scheme in high-frequency domain. Simulation results demonstrate high accuracy and robustness comparing to VD design.

Integration of electromagnetic induction sensor data in soil sampling scheme optimization using simulated annealing.

PubMed

Barca, E; Castrignanò, A; Buttafuoco, G; De Benedetto, D; Passarella, G

2015-07-01

Soil survey is generally time-consuming, labor-intensive, and costly. Optimization of sampling scheme allows one to reduce the number of sampling points without decreasing or even increasing the accuracy of investigated attribute. Maps of bulk soil electrical conductivity (EC a ) recorded with electromagnetic induction (EMI) sensors could be effectively used to direct soil sampling design for assessing spatial variability of soil moisture. A protocol, using a field-scale bulk EC a survey, has been applied in an agricultural field in Apulia region (southeastern Italy). Spatial simulated annealing was used as a method to optimize spatial soil sampling scheme taking into account sampling constraints, field boundaries, and preliminary observations. Three optimization criteria were used. the first criterion (minimization of mean of the shortest distances, MMSD) optimizes the spreading of the point observations over the entire field by minimizing the expectation of the distance between an arbitrarily chosen point and its nearest observation; the second criterion (minimization of weighted mean of the shortest distances, MWMSD) is a weighted version of the MMSD, which uses the digital gradient of the grid EC a data as weighting function; and the third criterion (mean of average ordinary kriging variance, MAOKV) minimizes mean kriging estimation variance of the target variable. The last criterion utilizes the variogram model of soil water content estimated in a previous trial. The procedures, or a combination of them, were tested and compared in a real case. Simulated annealing was implemented by the software MSANOS able to define or redesign any sampling scheme by increasing or decreasing the original sampling locations. The output consists of the computed sampling scheme, the convergence time, and the cooling law, which can be an invaluable support to the process of sampling design. The proposed approach has found the optimal solution in a reasonable computation time. The use of bulk EC a gradient as an exhaustive variable, known at any node of an interpolation grid, has allowed the optimization of the sampling scheme, distinguishing among areas with different priority levels.

Dependence of B1+ and B1- Field Patterns of Surface Coils on the Electrical Properties of the Sample and the MR Operating Frequency.

PubMed

Vaidya, Manushka V; Collins, Christopher M; Sodickson, Daniel K; Brown, Ryan; Wiggins, Graham C; Lattanzi, Riccardo

2016-02-01

In high field MRI, the spatial distribution of the radiofrequency magnetic ( B 1 ) field is usually affected by the presence of the sample. For hardware design and to aid interpretation of experimental results, it is important both to anticipate and to accurately simulate the behavior of these fields. Fields generated by a radiofrequency surface coil were simulated using dyadic Green's functions, or experimentally measured over a range of frequencies inside an object whose electrical properties were varied to illustrate a variety of transmit [Formula: see text] and receive [Formula: see text] field patterns. In this work, we examine how changes in polarization of the field and interference of propagating waves in an object can affect the B 1 spatial distribution. Results are explained conceptually using Maxwell's equations and intuitive illustrations. We demonstrate that the electrical conductivity alters the spatial distribution of distinct polarized components of the field, causing "twisted" transmit and receive field patterns, and asymmetries between [Formula: see text] and [Formula: see text]. Additionally, interference patterns due to wavelength effects are observed at high field in samples with high relative permittivity and near-zero conductivity, but are not present in lossy samples due to the attenuation of propagating EM fields. This work provides a conceptual framework for understanding B 1 spatial distributions for surface coils and can provide guidance for RF engineers.

Temporal and spatial resolution required for imaging myocardial function

NASA Astrophysics Data System (ADS)

Eusemann, Christian D.; Robb, Richard A.

2004-05-01

4-D functional analysis of myocardial mechanics is an area of significant interest and research in cardiology and vascular/interventional radiology. Current multidimensional analysis is limited by insufficient temporal resolution of x-ray and magnetic resonance based techniques, but recent improvements in system design holds hope for faster and higher resolution scans to improve images of moving structures allowing more accurate functional studies, such as in the heart. This paper provides a basis for the requisite temporal and spatial resolution for useful imaging during individual segments of the cardiac cycle. Multiple sample rates during systole and diastole are compared to determine an adequate sample frequency to reduce regional myocardial tracking errors. Concurrently, out-of-plane resolution has to be sufficiently high to minimize partial volume effect. Temporal resolution and out-of-plane spatial resolution are related factors that must be considered together. The data used for this study is a DSR dynamic volume image dataset with high temporal and spatial resolution using implanted fiducial markers to track myocardial motion. The results of this study suggest a reduced exposure and scan time for x-ray and magnetic resonance imaging methods, since a lower sample rate during systole is sufficient, whereas the period of rapid filling during diastole requires higher sampling. This could potentially reduce the cost of these procedures and allow higher patient throughput.

Mesoscale spatial variability of selected aquatic invertebrate community metrics from a minimally impaired stream segment

USGS Publications Warehouse

Gebler, J.B.

2004-01-01

The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

USGS Publications Warehouse

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

2005-01-01

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Diffractive optics for combined spatial- and mode- division demultiplexing of optical vortices: design, fabrication and optical characterization.

PubMed

Ruffato, Gianluca; Massari, Michele; Romanato, Filippo

2016-04-20

During the last decade, the orbital angular momentum (OAM) of light has attracted growing interest as a new degree of freedom for signal channel multiplexing in order to increase the information transmission capacity in today's optical networks. Here we present the design, fabrication and characterization of phase-only diffractive optical elements (DOE) performing mode-division (de)multiplexing (MDM) and spatial-division (de)multiplexing (SDM) at the same time. Samples have been fabricated with high-resolution electron-beam lithography patterning a polymethylmethacrylate (PMMA) resist layer spun over a glass substrate. Different DOE designs are presented for the sorting of optical vortices differing in either OAM content or beam size in the optical regime, with different steering geometries in far-field. These novel DOE designs appear promising for telecom applications both in free-space and in multi-core fibers propagation.

Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs.

PubMed

Rigamonti, Ivo E; Brambilla, Carla; Colleoni, Emanuele; Jermini, Mauro; Trivellone, Valeria; Baumgärtner, Johann

2016-04-01

The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.

BAYESIAN ENTROPY FOR SPATIAL SAMPLING DESIGN OF ENVIRONMENTAL DATA

EPA Science Inventory

Particulate Matter (PM) has been linked to widespread public health effects, including a range of serious respiratory and cardiovascular problems, and to reduced visibility in may parts of the United States, see the Environmental Protection Agency (EPA) report (2004) and relevant...

Optical design of the lightning imager for MTG

NASA Astrophysics Data System (ADS)

Lorenzini, S.; Bardazzi, R.; Di Giampietro, M.; Feresin, F.; Taccola, M.; Cuevas, L. P.

2017-11-01

The Lightning Imager for Meteosat Third Generation is an optical payload with on-board data processing for the detection of lightning. The instrument will provide a global monitoring of lightning events over the full Earth disk from geostationary orbit and will operate in day and night conditions. The requirements of the large field of view together with the high detection efficiency with small and weak optical pulses superimposed to a much brighter and highly spatial and temporal variable background (full operation during day and night conditions, seasonal variations and different albedos between clouds oceans and lands) are driving the design of the optical instrument. The main challenge is to distinguish a true lightning from false events generated by random noise (e.g. background shot noise) or sun glints diffusion or signal variations originated by microvibrations. This can be achieved thanks to a `multi-dimensional' filtering, simultaneously working on the spectral, spatial and temporal domains. The spectral filtering is achieved with a very narrowband filter centred on the bright lightning O2 triplet line (777.4 nm +/- 0.17 nm). The spatial filtering is achieved with a ground sampling distance significantly smaller (between 4 and 5 km at sub satellite pointing) than the dimensions of a typical lightning pulse. The temporal filtering is achieved by sampling continuously the Earth disk within a period close to 1 ms. This paper presents the status of the optical design addressing the trade-off between different configurations and detailing the design and the analyses of the current baseline. Emphasis is given to the discussion of the design drivers and the solutions implemented in particular concerning the spectral filtering and the optimisation of the signal to noise ratio.

Elemental mapping and microimaging by x-ray capillary optics.

PubMed

Hampai, D; Dabagov, S B; Cappuccio, G; Longoni, A; Frizzi, T; Cibin, G; Guglielmotti, V; Sala, M

2008-12-01

Recently, many experiments have highlighted the advantage of using polycapillary optics for x-ray fluorescence studies. We have developed a special confocal scheme for micro x-ray fluorescence measurements that enables us to obtain not only elemental mapping of the sample but also simultaneously its own x-ray imaging. We have designed the prototype of a compact x-ray spectrometer characterized by a spatial resolution of less than 100 microm for fluorescence and less than 10 microm for imaging. A couple of polycapillary lenses in a confocal configuration together with a silicon drift detector allow elemental studies of extended samples (approximately 3 mm) to be performed, while a CCD camera makes it possible to record an image of the same samples with 6 microm spatial resolution, which is limited only by the pixel size of the camera. By inserting a compound refractive lens between the sample and the CCD camera, we hope to develop an x-ray microscope for more enlarged images of the samples under test.

Flexible metamaterial absorbers for stealth applications at terahertz frequencies.

PubMed

Iwaszczuk, Krzysztof; Strikwerda, Andrew C; Fan, Kebin; Zhang, Xin; Averitt, Richard D; Jepsen, Peter Uhd

2012-01-02

We have wrapped metallic cylinders with strongly absorbing metamaterials. These resonant structures, which are patterned on flexible substrates, smoothly coat the cylinder and give it an electromagnetic response designed to minimize its radar cross section. We compare the normal-incidence, small-beam reflection coefficient with the measurement of the far-field bistatic radar cross section of the sample, using a quasi-planar THz wave with a beam diameter significantly larger than the sample dimensions. In this geometry we demonstrate a near-400-fold reduction of the radar cross section at the design frequency of 0.87 THz. In addition we discuss the effect of finite sample dimensions and the spatial dependence of the reflection spectrum of the metamaterial.

Horvitz-Thompson survey sample methods for estimating large-scale animal abundance

USGS Publications Warehouse

Samuel, M.D.; Garton, E.O.

1994-01-01

Large-scale surveys to estimate animal abundance can be useful for monitoring population status and trends, for measuring responses to management or environmental alterations, and for testing ecological hypotheses about abundance. However, large-scale surveys may be expensive and logistically complex. To ensure resources are not wasted on unattainable targets, the goals and uses of each survey should be specified carefully and alternative methods for addressing these objectives always should be considered. During survey design, the impoflance of each survey error component (spatial design, propofiion of detected animals, precision in detection) should be considered carefully to produce a complete statistically based survey. Failure to address these three survey components may produce population estimates that are inaccurate (biased low), have unrealistic precision (too precise) and do not satisfactorily meet the survey objectives. Optimum survey design requires trade-offs in these sources of error relative to the costs of sampling plots and detecting animals on plots, considerations that are specific to the spatial logistics and survey methods. The Horvitz-Thompson estimators provide a comprehensive framework for considering all three survey components during the design and analysis of large-scale wildlife surveys. Problems of spatial and temporal (especially survey to survey) heterogeneity in detection probabilities have received little consideration, but failure to account for heterogeneity produces biased population estimates. The goal of producing unbiased population estimates is in conflict with the increased variation from heterogeneous detection in the population estimate. One solution to this conflict is to use an MSE-based approach to achieve a balance between bias reduction and increased variation. Further research is needed to develop methods that address spatial heterogeneity in detection, evaluate the effects of temporal heterogeneity on survey objectives and optimize decisions related to survey bias and variance. Finally, managers and researchers involved in the survey design process must realize that obtaining the best survey results requires an interactive and recursive process of survey design, execution, analysis and redesign. Survey refinements will be possible as further knowledge is gained on the actual abundance and distribution of the population and on the most efficient techniques for detection animals.

Assessing species distribution using Google Street View: a pilot study with the Pine Processionary Moth.

PubMed

Rousselet, Jérôme; Imbert, Charles-Edouard; Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google Street View could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google Street View. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google Street View were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google Street View network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.

Assessing Species Distribution Using Google Street View: A Pilot Study with the Pine Processionary Moth

PubMed Central

Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre

2013-01-01

Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant. PMID:24130675

Optical Amplifier for Space Applications

NASA Technical Reports Server (NTRS)

Fork, Richard L.; Cole, Spencer T.; Gamble, Lisa J.; Diffey, William M.; Keys, Andrew S.

1999-01-01

We describe an optical amplifier designed to amplify a spatially sampled component of an optical wavefront to kilowatt average power. The goal is means for implementing a strategy of spatially segmenting a large aperture wavefront, amplifying the individual segments, maintaining the phase coherence of the segments by active means, and imaging the resultant amplified coherent field. Applications of interest are the transmission of space solar power over multi-megameter distances, as to distant spacecraft, or to remote sites with no preexisting power grid.

Using geostatistics to evaluate cleanup goals

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

Marcon, M.F.; Hopkins, L.P.

1995-12-01

Geostatistical analysis is a powerful predictive tool typically used to define spatial variability in environmental data. The information from a geostatistical analysis using kriging, a geostatistical. tool, can be taken a step further to optimize sampling location and frequency and help quantify sampling uncertainty in both the remedial investigation and remedial design at a hazardous waste site. Geostatistics were used to quantify sampling uncertainty in attainment of a risk-based cleanup goal and determine the optimal sampling frequency necessary to delineate the horizontal extent of impacted soils at a Gulf Coast waste site.

Spatiotemporal variability in biogenic gas dynamics in a subtropical peat soil at the laboratory scale is revealed using high-resolution ground-penetrating radar

NASA Astrophysics Data System (ADS)

Mustasaar, Mario; Comas, Xavier

2017-09-01

The importance of peatlands as sources of greenhouse gas emissions has been demonstrated in many studies during the last two decades. While most studies have shown the heterogeneous distribution of biogenic gas in peat soils at the field scale (sampling volumes in the order of meters), little information exists for submeter scales, particularly relevant to properly capture the dynamics of hot spots for gas accumulation and release when designing sampling routines with methods that use smaller (i.e., submeter) sampling volumes like flux chambers. In this study, ground-penetrating radar is used at the laboratory scale to evaluate biogenic gas dynamics at high spatial resolution (i.e., cm) in a peat monolith from the Everglades. The results indicate sharp changes (both spatially and temporally) in the dynamics of gas accumulation and release, representing hot spots for production and release of biogenic gases with surface areas ranging between 5 to 10 cm diameter and are associated with increases in porosity. Furthermore, changes in gas composition and inferred methane (CH4) and carbon dioxide (CO2) fluxes also displayed a high spatiotemporal variability associated with hot spots, resulting in CH4 and CO2 flux estimates showing differences up to 1 order of magnitude during the same day for different parts of the sample. This work follows on recent studies in the Everglades and questions the appropriateness of spatial and temporal scales of measurement when defining gas dynamics by showing how flux values may change both spatially and temporarily even when considering submeter spatial scales.

Reactor for in situ measurements of spatially resolved kinetic data in heterogeneous catalysis

NASA Astrophysics Data System (ADS)

Horn, R.; Korup, O.; Geske, M.; Zavyalova, U.; Oprea, I.; Schlögl, R.

2010-06-01

The present work describes a reactor that allows in situ measurements of spatially resolved kinetic data in heterogeneous catalysis. The reactor design allows measurements up to temperatures of 1300 °C and 45 bar pressure, i.e., conditions of industrial relevance. The reactor involves reactants flowing through a solid catalyst bed containing a sampling capillary with a side sampling orifice through which a small fraction of the reacting fluid (gas or liquid) is transferred into an analytical device (e.g., mass spectrometer, gas chromatograph, high pressure liquid chromatograph) for quantitative analysis. The sampling capillary can be moved with μm resolution in or against flow direction to measure species profiles through the catalyst bed. Rotation of the sampling capillary allows averaging over several scan lines. The position of the sampling orifice is such that the capillary channel through the catalyst bed remains always occupied by the capillary preventing flow disturbance and fluid bypassing. The second function of the sampling capillary is to provide a well which can accommodate temperature probes such as a thermocouple or a pyrometer fiber. If a thermocouple is inserted in the sampling capillary and aligned with the sampling orifice fluid temperature profiles can be measured. A pyrometer fiber can be used to measure the temperature profile of the solid catalyst bed. Spatial profile measurements are demonstrated for methane oxidation on Pt and methane oxidative coupling on Li/MgO, both catalysts supported on reticulated α -Al2O3 foam supports.

Toward MRI microimaging of single biological cells

NASA Astrophysics Data System (ADS)

Seeber, Derek Allan

There is a great advantage in signal to noise ratio (SNR) that can be obtained in nuclear magnetic resonance (NMR) on very small samples (having spatial dimensions ˜100 mum or less) if one employs NMR "microcoils" that are of similarly small dimensions. These gains in SNR could enable magnetic resonance imaging (MRI) microscopy with spatial resolutions of ˜1--2 mum, much better than currently available. We report the design and testing of a NMR microcoil receiver apparatus, employing solenoidal microcoils of dimensions of tens to hundreds of microns, using an applied field of 9 Tesla (proton frequency 383 MHz). For the smallest receiver coils we attain sensitivity sufficient to observe proton NMR with SNR one in a single scan applied to ˜10 mum3 (10 fl) water sample, containing 7 x 1011 total proton spins. In addition to the NMR applications, microcoils have been applied to MRI producing images with spatial resolutions as low as 2 mum x 3.5 mum x 14.8 mum on phantom images of rods and beads. This resolution can be further improved. MRI imaging of small sample volumes requires significant hardware modifications and improvements, all of which are discussed. Specifically, MRI microscopy requires very strong (>10 T/m), rapidly switchable triaxial magnetic field gradients. We report the design and construction of such a triaxial gradient system, producing gradient substantially greater than 15 T/m in all three directions, x, y, and z (as high as 50 T/m for the x direction). The gradients are power by a custom designed power supply capable of providing currents in excess of 200 amps and switching times of less than 5 mus corresponding to slew rates of greater that 107 T/m/s. The gradients are adequately uniform (within 5% over a volume of 600 mum3) and sufficient for microcoil MRI of small samples.

The contribution of spatial ability to mathematics achievement in middle childhood.

PubMed

Gilligan, Katie A; Flouri, Eirini; Farran, Emily K

2017-11-01

Strong spatial skills are associated with success in science, technology, engineering, and mathematics (STEM) domains. Although there is convincing evidence that spatial skills are a reliable predictor of mathematical achievement in preschool children and in university students, there is a lack of research exploring associations between spatial and mathematics achievement during the primary school years. To address this question, this study explored associations between mathematics and spatial skills in children aged 5 and 7years. The study sample included 12,099 children who participated in both Wave 3 (mean age=5; 02 [years; months]) and Wave 4 (mean age=7; 03) of the Millennium Cohort Study. Measures included a standardised assessment of mathematics and the Pattern Construction subscale of the British Ability Scales II to assess intrinsic-dynamic spatial skills. Spatial skills at 5 and 7years of age explained a significant 8.8% of the variation in mathematics achievement at 7years, above that explained by other predictors of mathematics, including gender, socioeconomic status, ethnicity, and language skills. This percentage increased to 22.6% without adjustment for language skills. This study expands previous findings by using a large-scale longitudinal sample of primary school children, a population that has been largely omitted from previous research exploring associations between spatial ability and mathematics achievement. The finding that early and concurrent spatial skills contribute to mathematics achievement at 7years of age highlights the potential of spatial skills as a novel target in the design of mathematics interventions for children in this age range. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Environmental drivers of spatial variation in whole-tree transpiration in an aspen-dominated upland-to-wetland forest gradient

NASA Astrophysics Data System (ADS)

Loranty, Michael M.; Mackay, D. Scott; Ewers, Brent E.; Adelman, Jonathan D.; Kruger, Eric L.

2008-02-01

Assumed representative center-of-stand measurements are typical inputs to models that scale forest transpiration to stand and regional extents. These inputs do not consider gradients in transpiration at stand boundaries or along moisture gradients and therefore potentially bias the large-scale estimates. We measured half-hourly sap flux (JS) for 173 trees in a spatially explicit cyclic sampling design across a topographically controlled gradient between a forested wetland and upland forest in northern Wisconsin. Our analyses focused on three dominant species in the site: quaking aspen (Populus tremuloides Michx), speckled alder (Alnus incana (DuRoi) Spreng), and white cedar (Thuja occidentalis L.). Sapwood area (AS) was used to scale JS to whole tree transpiration (EC). Because spatial patterns imply underlying processes, geostatistical analyses were employed to quantify patterns of spatial autocorrelation across the site. A simple Jarvis type model parameterized using a Monte Carlo sampling approach was used to simulate EC (EC-SIM). EC-SIM was compared with observed EC(EC-OBS) and found to reproduce both the temporal trends and spatial variance of canopy transpiration. EC-SIM was then used to examine spatial autocorrelation as a function of environmental drivers. We found no spatial autocorrelation in JS across the gradient from forested wetland to forested upland. EC was spatially autocorrelated and this was attributed to spatial variation in AS which suggests species spatial patterns are important for understanding spatial estimates of transpiration. However, the range of autocorrelation in EC-SIM decreased linearly with increasing vapor pressure deficit, implying that consideration of spatial variation in the sensitivity of canopy stomatal conductance to D is also key to accurately scaling up transpiration in space.

The high throughput virtual slit enables compact, inexpensive Raman spectral imagers

NASA Astrophysics Data System (ADS)

Gooding, Edward; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

2018-02-01

Raman spectral imaging is increasingly becoming the tool of choice for field-based applications such as threat, narcotics and hazmat detection; air, soil and water quality monitoring; and material ID. Conventional fiber-coupled point source Raman spectrometers effectively interrogate a small sample area and identify bulk samples via spectral library matching. However, these devices are very slow at mapping over macroscopic areas. In addition, the spatial averaging performed by instruments that collect binned spectra, particularly when used in combination with orbital raster scanning, tends to dilute the spectra of trace particles in a mixture. Our design, employing free space line illumination combined with area imaging, reveals both the spectral and spatial content of heterogeneous mixtures. This approach is well suited to applications such as detecting explosives and narcotics trace particle detection in fingerprints. The patented High Throughput Virtual Slit1 is an innovative optical design that enables compact, inexpensive handheld Raman spectral imagers. HTVS-based instruments achieve significantly higher spectral resolution than can be obtained with conventional designs of the same size. Alternatively, they can be used to build instruments with comparable resolution to large spectrometers, but substantially smaller size, weight and unit cost, all while maintaining high sensitivity. When used in combination with laser line imaging, this design eliminates sample photobleaching and unwanted photochemistry while greatly enhancing mapping speed, all with high selectivity and sensitivity. We will present spectral image data and discuss applications that are made possible by low cost HTVS-enabled instruments.

Maternal working memory and reactive negativity in parenting.

PubMed

Deater-Deckard, Kirby; Sewell, Michael D; Petrill, Stephen A; Thompson, Lee A

2010-01-01

We examined the role of working memory in observed reactive parenting in a sample of 216 mothers and their same-sex twin children. The mothers and their children were observed completing two frustrating cooperation tasks during a visit to the home. The mothers worked one-on-one with each child separately. Mothers completed the Vocabulary (verbal), Block Design (spatial), and Digit Span (working memory) subtests of the Wechsler Adult Intelligence Scale-Third Edition. We used a within-family quasi-experimental design to estimate the magnitude of the association between sibling differences in observed challenging behaviors (i.e., opposition and distractibility) and the difference in the mother's negativity toward each child. As hypothesized, reactive negativity was evident only among mothers with poorer working memory. Verbal and spatial ability did not show this moderating effect. The effect was replicated in a post hoc secondary data analysis of a sample of adoptive mothers and sibling children. Results implicate working memory in the etiology of harsh reactive parenting.

The New Bedford Harbor Superfund Site Long Term ...

EPA Pesticide Factsheets

Background. New Bedford Harbor (NBH), located in southeastern Massachusetts, was designated as a marine Superfund site in 1983 due to sediment contamination by polychlorinated biphenyls (PCBs). Based on risks to human health and the environment, the first two phases of the site cleanup involved dredging PCB-contaminated sediments from the harbor. Therefore, a long-term monitoring program (LTM) was developed to measure spatial and temporal chemical and biological changes in sediment, water, and biota to assess the effects and effectiveness of the remedial activities. Approach. A systematic, probabilistic sampling design was used to select approximately 70 sediment sampling stations. Sediment was collected at each station and chemical (e.g., PCBs, metals), physical (e.g., grain size), and biological (e.g., benthic community) measurements were conducted on all samples. There have been six sample collections to date: 1993-baseline, 1995-post hot spot removal, 1999-prior to full scale dredging, and then at 5 year intervals: 2004, 2009, and 2014. Mussel (Mytilus edulis) bioaccumulation has also been measured twice yearly. Results. There is a decreasing spatial gradient in sediment PCB concentrations from the northern boundary (upper harbor) to the southern boundary (outer harbor) of the site. Along this same transect, there is an increase in biological condition (e.g., benthic community diversity). Temporally, the contaminant and biological gradients have been

Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

USGS Publications Warehouse

Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

2011-01-01

Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

Effect of site level environmental variables, spatial autocorrelation and sampling intensity on arthropod communities in an ancient temperate lowland woodland area.

PubMed

Horak, Jakub

2013-01-01

The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.

Spatial Statistical Models and Optimal Survey Design for Rapid Geophysical characterization of UXO Sites

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

G. Ostrouchov; W.E.Doll; D.A.Wolf

2003-07-01

Unexploded ordnance(UXO)surveys encompass large areas, and the cost of surveying these areas can be high. Enactment of earlier protocols for sampling UXO sites have shown the shortcomings of these procedures and led to a call for development of scientifically defensible statistical procedures for survey design and analysis. This project is one of three funded by SERDP to address this need.

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

USGS Publications Warehouse

Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.

2008-01-01

Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.

Patterns in Habitat and Fish Assemblages within Great Lakes Coastal Wetlands and Implications for Sampling Design

EPA Science Inventory

Discerning fish - habitat associations at a variety of spatial scales is relevant to evaluating stressor responses and assessment protocols in Great Lakes coastal wetlands. NMDS ordination of electrofishing catch-per-effort data identified an overriding influence of geography an...

Estimates of reservoir methane emissions based on a spatially ...

EPA Pesticide Factsheets

Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here we use a generalized random tessellation survey (GRTS) design to generate estimates of central tendency and variance at multiple spatial scales in a reservoir. GRTS survey designs are probabilistic and spatially balanced which eliminates bias associated with expert judgment in site selection. GRTS surveys also allow for variance estimates that account for spatial pattern in emission rates. Total CH4 emission rates (i.e. sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m-2 h-1 in open-waters, tributary associated areas, and the entire reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, USA. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine-lacustrine transition zones. Ebullition accounted for >90% of CH4 emission at all spatial scales. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence

Characterizing spatial structure of sediment E. coli populations to inform sampling design.

PubMed

Piorkowski, Gregory S; Jamieson, Rob C; Hansen, Lisbeth Truelstrup; Bezanson, Greg S; Yost, Chris K

2014-01-01

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p = 0.002) among monitoring sites during baseflow, and significant interactive effects (p = 0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D 10) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D 50) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.

On the importance of image formation optics in the design of infrared spectroscopic imaging systems

PubMed Central

Mayerich, David; van Dijk, Thomas; Walsh, Michael; Schulmerich, Matthew; Carney, P. Scott

2014-01-01

Infrared spectroscopic imaging provides micron-scale spatial resolution with molecular contrast. While recent work demonstrates that sample morphology affects the recorded spectrum, considerably less attention has been focused on the effects of the optics, including the condenser and objective. This analysis is extremely important, since it will be possible to understand effects on recorded data and provides insight for reducing optical effects through rigorous microscope design. Here, we present a theoretical description and experimental results that demonstrate the effects of commonly-employed cassegranian optics on recorded spectra. We first combine an explicit model of image formation and a method for quantifying and visualizing the deviations in recorded spectra as a function of microscope optics. We then verify these simulations with measurements obtained from spatially heterogeneous samples. The deviation of the computed spectrum from the ideal case is quantified via a map which we call a deviation map. The deviation map is obtained as a function of optical elements by systematic simulations. Examination of deviation maps demonstrates that the optimal optical configuration for minimal deviation is contrary to prevailing practice in which throughput is maximized for an instrument without a sample. This report should be helpful for understanding recorded spectra as a function of the optics, the analytical limits of recorded data determined by the optical design, and potential routes for optimization of imaging systems. PMID:24936526

On the importance of image formation optics in the design of infrared spectroscopic imaging systems.

PubMed

Mayerich, David; van Dijk, Thomas; Walsh, Michael J; Schulmerich, Matthew V; Carney, P Scott; Bhargava, Rohit

2014-08-21

Infrared spectroscopic imaging provides micron-scale spatial resolution with molecular contrast. While recent work demonstrates that sample morphology affects the recorded spectrum, considerably less attention has been focused on the effects of the optics, including the condenser and objective. This analysis is extremely important, since it will be possible to understand effects on recorded data and provides insight for reducing optical effects through rigorous microscope design. Here, we present a theoretical description and experimental results that demonstrate the effects of commonly-employed cassegranian optics on recorded spectra. We first combine an explicit model of image formation and a method for quantifying and visualizing the deviations in recorded spectra as a function of microscope optics. We then verify these simulations with measurements obtained from spatially heterogeneous samples. The deviation of the computed spectrum from the ideal case is quantified via a map which we call a deviation map. The deviation map is obtained as a function of optical elements by systematic simulations. Examination of deviation maps demonstrates that the optimal optical configuration for minimal deviation is contrary to prevailing practice in which throughput is maximized for an instrument without a sample. This report should be helpful for understanding recorded spectra as a function of the optics, the analytical limits of recorded data determined by the optical design, and potential routes for optimization of imaging systems.

Spatial Variation in Particulate Matter Components over a Large Urban Area

PubMed Central

Fruin, Scott; Urman, Robert; Lurmann, Fred; McConnell, Rob; Gauderman, James; Rappaport, Ed; Franklin, Meredith; Gilliland, Frank D.; Shafer, Martin; Gorski, Patrick; Avol, Ed

2014-01-01

To characterize exposures to particulate matter (PM) and its components, we performed a large sampling study of small-scale spatial variation in size-resolved particle mass and composition. PM was collected in size ranges of < 0.2, 0.2-to-2.5, and 2.5-to-10 μm on a scale of 100s to 1000s of meters to capture local sources. Within each of eight Southern California communities, up to 29 locations were sampled for rotating, month-long integrated periods at two different times of the year, six months apart, from Nov 2008 through Dec 2009. Additional sampling was conducted at each community’s regional monitoring station to provide temporal coverage over the sampling campaign duration. Residential sampling locations were selected based on a novel design stratified by high- and low-predicted traffic emissions and locations over- and under-predicted from previous dispersion model and sampling comparisons. Primary vehicle emissions constituents, such as elemental carbon (EC), showed much stronger patterns of association with traffic than pollutants with significant secondary formation, such as PM2.5 or water soluble organic carbon. Associations were also stronger during cooler times of the year (Oct through Mar). Primary pollutants also showed greater within-community spatial variation compared to pollutants with secondary formation contributions. For example, the average cool-season community mean and standard deviation (SD) for EC were 1.1 and 0.17 μg/m3, respectively, giving a coefficient of variation (CV) of 18%. For PM2.5, average mean and SD were 14 and 1.3 μg/m3, respectively, with a CV of 9%. We conclude that within-community spatial differences are important for accurate exposure assessment of traffic-related pollutants. PMID:24578605

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.

Cytometer on a chip

NASA Technical Reports Server (NTRS)

Lynes, Michael A. (Inventor); Fernandez, Salvador M. (Inventor)

2010-01-01

An assay technique for label-free, highly parallel, qualitative and quantitative detection of specific cell populations in a sample and for assessing cell functional status, cell-cell interactions and cellular responses to drugs, environmental toxins, bacteria, viruses and other factors that may affect cell function. The technique includes a) creating a first array of binding regions in a predetermined spatial pattern on a sensor surface capable of specifically binding the cells to be assayed; b) creating a second set of binding regions in specific spatial patterns relative to the first set designed to efficiently capture potential secreted or released products from cells captured on the first set of binding regions; c) contacting the sensor surface with the sample, and d) simultaneously monitoring the optical properties of all the binding regions of the sensor surface to determine the presence and concentration of specific cell populations in the sample and their functional status by detecting released or secreted bioproducts.

Spatial mapping of lead, arsenic, iron, and polycyclic aromatic hydrocarbon soil contamination in Sydney, Nova Scotia: community impact from the coke ovens and steel plant.

PubMed

Lambert, Timothy W; Boehmer, Jennifer; Feltham, Jason; Guyn, Lindsay; Shahid, Rizwan

2011-01-01

This paper presents spatial maps of the arsenic, lead, and polycyclic aromatic hydrocarbon (PAH) soil contamination in Sydney, Nova Scotia, Canada. The spatial maps were designed to create exposure cohorts to help understand the observed increase in health effects. To assess whether contamination can be a proxy for exposures, the following hypothesis was tested: residential soils were impacted by the coke oven and steel plant industrial complex. The spatial map showed contaminants are centered on the industrial facility, significantly correlated, and exceed Canadian health risk-based soil quality guidelines. Core samples taken at 5-cm intervals suggest a consistent deposition over time. The concentrations in Sydney significantly exceed background Sydney soil concentrations, and are significantly elevated compared with North Sydney, an adjacent industrial community. The contaminant spatial maps will also be useful for developing cohorts of exposure and guiding risk management decisions.

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.

PubMed

Xu, Ruilian; Tang, Jun; Deng, Quantong; He, Wan; Sun, Xiujie; Xia, Ligang; Cheng, Zhiqiang; He, Lisheng; You, Shuyuan; Hu, Jintao; Fu, Yuxiang; Zhu, Jian; Chen, Yixin; Gao, Weina; He, An; Guo, Zhengyu; Lin, Lin; Li, Hua; Hu, Chaofeng; Tian, Ruijun

2018-05-01

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm 2 and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm 2 and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

Comparison of two confocal micro-XRF spectrometers with different design aspects

PubMed Central

Smolek, S; Nakazawa, T; Tabe, A; Nakano, K; Tsuji, K; Streli, C; Wobrauschek, P

2014-01-01

Two different confocal micro X-ray fluorescence spectrometers have been developed and installed at Osaka City University and the Vienna University of Technology Atominstitut. The Osaka City University system is a high resolution spectrometer operating in air. The Vienna University of Technology Atominstitut spectrometer has a lower spatial resolution but is optimized for light element detection and operates under vacuum condition. The performance of both spectrometers was compared. In order to characterize the spatial resolution, a set of nine specially prepared single element thin film reference samples (500 nm in thickness, Al, Ti, Cr, Fe Ni, Cu, Zr, Mo, and Au) was used. Lower limits of detection were determined using the National Institute of Standards and Technology standard reference material glass standard 1412. A paint layer sample (cultural heritage application) and paint on automotive steel samples were analyzed with both instruments. The depth profile information was acquired by scanning the sample perpendicular to the surface. © 2013 The Authors. X-Ray Spectrometry published by John Wiley & Sons, Ltd. PMID:26430286

Comparison of two confocal micro-XRF spectrometers with different design aspects.

PubMed

Smolek, S; Nakazawa, T; Tabe, A; Nakano, K; Tsuji, K; Streli, C; Wobrauschek, P

2014-03-01

Two different confocal micro X-ray fluorescence spectrometers have been developed and installed at Osaka City University and the Vienna University of Technology Atominstitut. The Osaka City University system is a high resolution spectrometer operating in air. The Vienna University of Technology Atominstitut spectrometer has a lower spatial resolution but is optimized for light element detection and operates under vacuum condition. The performance of both spectrometers was compared. In order to characterize the spatial resolution, a set of nine specially prepared single element thin film reference samples (500 nm in thickness, Al, Ti, Cr, Fe Ni, Cu, Zr, Mo, and Au) was used. Lower limits of detection were determined using the National Institute of Standards and Technology standard reference material glass standard 1412. A paint layer sample (cultural heritage application) and paint on automotive steel samples were analyzed with both instruments. The depth profile information was acquired by scanning the sample perpendicular to the surface. © 2013 The Authors. X-Ray Spectrometry published by John Wiley & Sons, Ltd.

Statistical approaches used to assess and redesign surface water-quality-monitoring networks.

PubMed

Khalil, B; Ouarda, T B M J

2009-11-01

An up-to-date review of the statistical approaches utilized for the assessment and redesign of surface water quality monitoring (WQM) networks is presented. The main technical aspects of network design are covered in four sections, addressing monitoring objectives, water quality variables, sampling frequency and spatial distribution of sampling locations. This paper discusses various monitoring objectives and related procedures used for the assessment and redesign of long-term surface WQM networks. The appropriateness of each approach for the design, contraction or expansion of monitoring networks is also discussed. For each statistical approach, its advantages and disadvantages are examined from a network design perspective. Possible methods to overcome disadvantages and deficiencies in the statistical approaches that are currently in use are recommended.

Static sampling of dynamic processes - a paradox?

NASA Astrophysics Data System (ADS)

Mälicke, Mirko; Neuper, Malte; Jackisch, Conrad; Hassler, Sibylle; Zehe, Erwin

2017-04-01

Environmental systems monitoring aims at its core at the detection of spatio-temporal patterns of processes and system states, which is a pre-requisite for understanding and explaining their baffling heterogeneity. Most observation networks rely on distributed point sampling of states and fluxes of interest, which is combined with proxy-variables from either remote sensing or near surface geophysics. The cardinal question on the appropriate experimental design of such a monitoring network has up to now been answered in many different ways. Suggested approaches range from sampling in a dense regular grid using for the so-called green machine, transects along typical catenas, clustering of several observations sensors in presumed functional units or HRUs, arrangements of those cluster along presumed lateral flow paths to last not least a nested, randomized stratified arrangement of sensors or samples. Common to all these approaches is that they provide a rather static spatial sampling, while state variables and their spatial covariance structure dynamically change in time. It is hence of key interest how much of our still incomplete understanding stems from inappropriate sampling and how much needs to be attributed to an inappropriate analysis of spatial data sets. We suggest that it is much more promising to analyze the spatial variability of processes, for instance changes in soil moisture values, than to investigate the spatial variability of soil moisture states themselves. This is because wetting of the soil, reflected in a soil moisture increase, is causes by a totally different meteorological driver - rainfall - than drying of the soil. We hence propose that the rising and the falling limbs of soil moisture time series belong essentially to different ensembles, as they are influenced by different drivers. Positive and negative temporal changes in soil moisture need, hence, to be analyzed separately. We test this idea using the CAOS data set as a benchmark. Specifically, we expect the covariance structure of the positive temporal changes of soil moisture to be dominated by the spatial structure of rain- and through-fall and saturated hydraulic conductivity. The covariance in temporarily decreasing soil moisture during radiation driven conditions is expect to be dominated by the spatial structure of retention properties and plant transpiration. An analysis of soil moisture changes has furthermore the advantage that those are free from systematic measurement errors.

Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

EPA Science Inventory

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...

USING BAYESIAN SPATIAL MODELS TO FACILITATE WATER QUALITY MONITORING

EPA Science Inventory

The Clean Water Act of 1972 requires states to monitor the quality of their surface water. The number of sites sampled on streams and rivers varies widely by state. A few states are now using probability survey designs to select sites, while most continue to rely on other proce...

Quantifying Urban Watershed Stressor Gradients and Evaluating How Different Land Cover Datasets Affect Stream Management

EPA Science Inventory

We used a gradient (divided into impervious cover categories), spatially-balanced, random design (1) to sample streams along an impervious cover gradient in a large coastal watershed, (2) to characterize relationships between water chemistry and land cover, and (3) to document di...

Model-based inference for small area estimation with sampling weights

PubMed Central

Vandendijck, Y.; Faes, C.; Kirby, R.S.; Lawson, A.; Hens, N.

2017-01-01

Obtaining reliable estimates about health outcomes for areas or domains where only few to no samples are available is the goal of small area estimation (SAE). Often, we rely on health surveys to obtain information about health outcomes. Such surveys are often characterised by a complex design, stratification, and unequal sampling weights as common features. Hierarchical Bayesian models are well recognised in SAE as a spatial smoothing method, but often ignore the sampling weights that reflect the complex sampling design. In this paper, we focus on data obtained from a health survey where the sampling weights of the sampled individuals are the only information available about the design. We develop a predictive model-based approach to estimate the prevalence of a binary outcome for both the sampled and non-sampled individuals, using hierarchical Bayesian models that take into account the sampling weights. A simulation study is carried out to compare the performance of our proposed method with other established methods. The results indicate that our proposed method achieves great reductions in mean squared error when compared with standard approaches. It performs equally well or better when compared with more elaborate methods when there is a relationship between the responses and the sampling weights. The proposed method is applied to estimate asthma prevalence across districts. PMID:28989860

Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

NASA Astrophysics Data System (ADS)

Xiao, T.

2012-12-01

One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

Sampling design trade-offs in occupancy studies with imperfect detection: examples and software

USGS Publications Warehouse

Bailey, L.L.; Hines, J.E.; Nichols, J.D.

2007-01-01

Researchers have used occupancy, or probability of occupancy, as a response or state variable in a variety of studies (e.g., habitat modeling), and occupancy is increasingly favored by numerous state, federal, and international agencies engaged in monitoring programs. Recent advances in estimation methods have emphasized that reliable inferences can be made from these types of studies if detection and occupancy probabilities are simultaneously estimated. The need for temporal replication at sampled sites to estimate detection probability creates a trade-off between spatial replication (number of sample sites distributed within the area of interest/inference) and temporal replication (number of repeated surveys at each site). Here, we discuss a suite of questions commonly encountered during the design phase of occupancy studies, and we describe software (program GENPRES) developed to allow investigators to easily explore design trade-offs focused on particularities of their study system and sampling limitations. We illustrate the utility of program GENPRES using an amphibian example from Greater Yellowstone National Park, USA.

Temporal and Spatial Variation of Soil Bacteria Richness, Composition, and Function in a Neotropical Rainforest

PubMed Central

Kivlin, Stephanie N; Hawkes, Christine V

2016-01-01

The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change. PMID:27391450

Temporal and Spatial Variation of Soil Bacteria Richness, Composition, and Function in a Neotropical Rainforest.

PubMed

Kivlin, Stephanie N; Hawkes, Christine V

2016-01-01

The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change.

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

High-resolution imaging of magnetic fields using scanning superconducting quantum interference device (SQUID) microscopy

NASA Astrophysics Data System (ADS)

Fong de Los Santos, Luis E.

Development of a scanning superconducting quantum interference device (SQUID) microscope system with interchangeable sensor configurations for imaging magnetic fields of room-temperature (RT) samples with sub-millimeter resolution. The low-critical-temperature (Tc) niobium-based monolithic SQUID sensor is mounted in the tip of a sapphire rod and thermally anchored to the cryostat helium reservoir. A 25 mum sapphire window separates the vacuum space from the RT sample. A positioning mechanism allows adjusting the sample-to-sensor spacing from the top of the Dewar. I have achieved a sensor-to-sample spacing of 100 mum, which could be maintained for periods of up to 4 weeks. Different SQUID sensor configurations are necessary to achieve the best combination of spatial resolution and field sensitivity for a given magnetic source. For imaging thin sections of geological samples, I used a custom-designed monolithic low-Tc niobium bare SQUID sensor, with an effective diameter of 80 mum, and achieved a field sensitivity of 1.5 pT/Hz1/2 and a magnetic moment sensitivity of 5.4 x 10-18 Am2/Hz1/2 at a sensor-to-sample spacing of 100 mum in the white noise region for frequencies above 100 Hz. Imaging action currents in cardiac tissue requires higher field sensitivity, which can only be achieved by compromising spatial resolution. I developed a monolithic low-Tc niobium multiloop SQUID sensor, with sensor sizes ranging from 250 mum to 1 mm, and achieved sensitivities of 480 - 180 fT/Hz1/2 in the white noise region for frequencies above 100 Hz, respectively. For all sensor configurations, the spatial resolution was comparable to the effective diameter and limited by the sensor-to-sample spacing. Spatial registration allowed us to compare high-resolution images of magnetic fields associated with action currents and optical recordings of transmembrane potentials to study the bidomain nature of cardiac tissue or to match petrography to magnetic field maps in thin sections of geological samples.

Reduction of spatial distribution of risk factors for transportation of contaminants released by coal mining activities.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-09-15

It is reported that water-energy nexus composes two of the biggest development and human health challenges. In the present study we presented a Risk Potential Index (RPI) model which encapsulates Source, Vector (Transport), and Target risks for forecasting surface water contamination. The main aim of the model is to identify critical surface water risk zones for an open cast mining environment, taking Jharia Coalfield, India as the study area. The model also helps in feasible sampling design. Based on spatial analysis various risk zones were successfully delineated. Monthly RPI distribution revealed that the risk of surface water contamination was highest during the monsoon months. Surface water samples were analysed to validate the model. A GIS based alternative management option was proposed to reduce surface water contamination risk and observed 96% and 86% decrease in the spatial distribution of very high risk areas for the months June and July respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Near-Infrared Spatially Resolved Spectroscopy for Tablet Quality Determination.

PubMed

Igne, Benoît; Talwar, Sameer; Feng, Hanzhou; Drennen, James K; Anderson, Carl A

2015-12-01

Near-infrared (NIR) spectroscopy has become a well-established tool for the characterization of solid oral dosage forms manufacturing processes and finished products. In this work, the utility of a traditional single-point NIR measurement was compared with that of a spatially resolved spectroscopic (SRS) measurement for the determination of tablet assay. Experimental designs were used to create samples that allowed for calibration models to be developed and tested on both instruments. Samples possessing a poor distribution of ingredients (highly heterogeneous) were prepared by under-blending constituents prior to compaction to compare the analytical capabilities of the two NIR methods. The results indicate that SRS can provide spatial information that is usually obtainable only through imaging experiments for the determination of local heterogeneity and detection of abnormal tablets that would not be detected with single-point spectroscopy, thus complementing traditional NIR measurement systems for in-line, and in real-time tablet analysis. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Profiling of patterned metal layers by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS)

NASA Astrophysics Data System (ADS)

Bi, Melody; Ruiz, Antonio M.; Gornushkin, Igor; Smith, Ben W.; Winefordner, James D.

2000-02-01

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used for profiling patterned thin metal layers on a polymer/silicon substrate. The parameters of the laser and ICP-MS operating conditions have been studied and optimized for this purpose. A new laser ablation chamber was designed and built to achieve the best spatial resolution. The results of the profiling by LA-ICP-MS were compared to those obtained from a laser ablation optical emission spectrometry (LA-OES) instrument, which measured the emission of the plasma at the sample surface, and thus, eliminated the time delay caused by the sample transport into the ICP-MS system. Emission spectra gave better spatial resolution than mass spectra. However, LA-ICP-MS provided much better sensitivity and was able to profile thin metal layers (on the order of a few nanometers) on the silicon surface. A lateral spatial resolution of 45 μm was achieved.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

A Robot Equipped with a High-Speed LSPR Gas Sensor Module for Collecting Spatial Odor Information from On-Ground Invisible Odor Sources.

PubMed

Yang, Zhongyuan; Sassa, Fumihiro; Hayashi, Kenshi

2018-06-22

Improving the efficiency of detecting the spatial distribution of gas information with a mobile robot is a great challenge that requires rapid sample collection, which is basically determined by the speed of operation of gas sensors. The present work developed a robot equipped with a high-speed gas sensor module based on localized surface plasmon resonance. The sensor module is designed to sample gases from an on-ground odor source, such as a footprint material or artificial odor marker, via a fine sampling tubing. The tip of the sampling tubing was placed close to the ground to reduce the sampling time and the effect of natural gas diffusion. On-ground ethanol odor sources were detected by the robot at high resolution (i.e., 2.5 cm when the robot moved at 10 cm/s), and the reading of gas information was demonstrated experimentally. This work may help in the development of environmental sensing robots, such as the development of odor source mapping and multirobot systems with pheromone tracing.

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales-review and recommendations.

PubMed

Vanguelova, E I; Bonifacio, E; De Vos, B; Hoosbeek, M R; Berger, T W; Vesterdal, L; Armolaitis, K; Celi, L; Dinca, L; Kjønaas, O J; Pavlenda, P; Pumpanen, J; Püttsepp, Ü; Reidy, B; Simončič, P; Tobin, B; Zhiyanski, M

2016-11-01

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.

Drivers and Spatio-Temporal Extent of Hyporheic Patch Variation: Implications for Sampling

PubMed Central

Braun, Alexander; Auerswald, Karl; Geist, Juergen

2012-01-01

The hyporheic zone in stream ecosystems is a heterogeneous key habitat for species across many taxa. Consequently, it attracts high attention among freshwater scientists, but generally applicable guidelines on sampling strategies are lacking. Thus, the objective of this study was to develop and validate such sampling guidelines. Applying geostatistical analysis, we quantified the spatio-temporal variability of parameters, which characterize the physico-chemical substratum conditions in the hyporheic zone. We investigated eight stream reaches in six small streams that are typical for the majority of temperate areas. Data was collected on two occasions in six stream reaches (development data), and once in two additional reaches, after one year (validation data). In this study, the term spatial variability refers to patch contrast (patch to patch variance) and patch size (spatial extent of a patch). Patch contrast of hyporheic parameters (specific conductance, pH and dissolved oxygen) increased with macrophyte cover (r2 = 0.95, p<0.001), while patch size of hyporheic parameters decreased from 6 to 2 m with increasing sinuosity of the stream course (r2 = 0.91, p<0.001), irrespective of the time of year. Since the spatial variability of hyporheic parameters varied between stream reaches, our results suggest that sampling design should be adapted to suit specific stream reaches. The distance between sampling sites should be inversely related to the sinuosity, while the number of samples should be related to macrophyte cover. PMID:22860053

Spatial and Temporal Monitoring Resolutions for CO2 Leakage Detection at Carbon Storage Sites

NASA Astrophysics Data System (ADS)

Yang, Y. M.; Dilmore, R. M.; Daley, T. M.; Carroll, S.; Mansoor, K.; Gasperikova, E.; Harbert, W.; Wang, Z.; Bromhal, G. S.; Small, M.

2016-12-01

Different leakage monitoring techniques offer different strengths in detection sensitivity, coverage, feedback time, cost, and technology availability, such that they may complement each other when applied together. This research focuses on quantifying the spatial coverage and temporal resolution of detection response for several geophysical remote monitoring and direct groundwater monitoring techniques for an optimal monitoring plan for CO2 leakage detection. Various monitoring techniques with different monitoring depths are selected: 3D time-lapse seismic survey, wellbore pressure, groundwater chemistry and soil gas. The spatial resolution in terms of leakage detectability is quantified through the effective detection distance between two adjacent monitors, given the magnitude of leakage and specified detection probability. The effective detection distances are obtained either from leakage simulations with various monitoring densities or from information garnered from field test data. These spatial leakage detection resolutions are affected by physically feasible monitoring design and detection limits. Similarly, the temporal resolution, in terms of leakage detectability, is quantified through the effective time to positive detection of a given size of leak and a specified detection probability, again obtained either from representative leakage simulations with various monitoring densities or from field test data. The effective time to positive detection is also affected by operational feedback time (associated with sampling, sample analysis and data interpretation), with values obtained mainly through expert interviews and literature review. In additional to the spatial and temporal resolutions of these monitoring techniques, the impact of CO2 plume migration speed and leakage detection sensitivity of each monitoring technique are also discussed with consideration of how much monitoring is necessary for effective leakage detection and how these monitoring techniques can be better combined in a time-space framework. The results of the spatial and temporal leakage detection resolutions for several geophysical monitoring techniques and groundwater monitoring are summarized to inform future monitoring designs at carbon storage sites.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

Analysis of Extreme Snow Water Equivalent Data in Central New Hampshire

NASA Astrophysics Data System (ADS)

Vuyovich, C.; Skahill, B. E.; Kanney, J. F.; Carr, M.

2017-12-01

Heavy snowfall and snowmelt-related events have been linked to widespread flooding and damages in many regions of the U.S. Design of critical infrastructure in these regions requires spatial estimates of extreme snow water equivalent (SWE). In this study, we develop station specific and spatially explicit estimates of extreme SWE using data from fifteen snow sampling stations maintained by the New Hampshire Department of Environmental Services. The stations are located in the Mascoma, Pemigewasset, Winnipesaukee, Ossipee, Salmon Falls, Lamprey, Sugar, and Isinglass basins in New Hampshire. The average record length for the fifteen stations is approximately fifty-nine years. The spatial analysis of extreme SWE involves application of two Bayesian Hierarchical Modeling methods, one that assumes conditional independence, and another which uses the Smith max-stable process model to account for spatial dependence. We also apply additional max-stable process models, albeit not in a Bayesian framework, that better model the observed dependence among the extreme SWE data. The spatial process modeling leverages readily available and relevant spatially explicit covariate data. The noted additional max-stable process models also used the nonstationary winter North Atlantic Oscillation index, which has been observed to influence snowy weather along the east coast of the United States. We find that, for this data set, SWE return level estimates are consistently higher when derived using methods which account for the observed spatial dependence among the extreme data. This is particularly significant for design scenarios of relevance for critical infrastructure evaluation.

Spanish Transcultural Adaptation and Validity of the Behavioral Inattention Test

PubMed Central

Sánchez-Cabeza, Ángel; Huertas-Hoyas, Elisabet; Máximo-Bocanegra, Nuria; Rosa María Martínez-Piédrola; Pérez-de-Heredia-Torres, Marta

2017-01-01

Objective To adapt, validate, and translate the Behavioral Inattention Test as an assessment tool for Spanish individuals with unilateral spatial neglect. Design A cross-sectional descriptive study. Setting University laboratories. Participants A sample of 75 Spanish stroke patients and 18 healthy control subjects. Interventions Not applicable. Main Outcome Measures The Behavioral Inattention Test. Results The Spanish version of the Behavioral Inattention Test shows a high degree of reliability both in the complete test (α = .90) and in the conventional (α = .93) and behavioral subtests (α = .75). The concurrent validity between the total conventional and behavioral scores was high (r = −.80; p < 0.001). Significant differences were found between patients with and without unilateral spatial neglect (p < 0.001). In the comparison between right and left damaged sides, differences were found in all items, except for article reading (p = 0.156) and card sorting (p = 0.117). Conclusions This measure is a useful tool for evaluating unilateral spatial neglect as it provides information on everyday problems. The BIT discriminates between stroke patients with and without unilateral spatial neglect. This measure constitutes a reliable tool for the diagnosis, planning, performance, and design of specific treatment programs intended to improve the functionality and quality of life of people with unilateral spatial neglect. PMID:29097959

A novel x-ray detector design with higher DQE and reduced aliasing: Theoretical analysis of x-ray reabsoprtion in detector converter material

NASA Astrophysics Data System (ADS)

Nano, Tomi; Escartin, Terenz; Karim, Karim S.; Cunningham, Ian A.

2016-03-01

The ability to improve visualization of structural information in digital radiography without increasing radiation exposures requires improved image quality across all spatial frequencies, especially at high frequencies. The detective quantum efficiency (DQE) as a function of spatial frequency quantifies image quality given by an x-ray detector. We present a method of increasing DQE at high spatial frequencies by improving the modulation transfer function (MTF) and reducing noise aliasing. The Apodized Aperature Pixel (AAP) design uses a detector with micro-elements to synthesize desired pixels and provide higher DQE than conventional detector designs. A cascaded system analysis (CSA) that incorporates x-ray interactions is used for comparison of the theoretical MTF, noise power spectrum (NPS), and DQE. Signal and noise transfer through the converter material is shown to consist of correlated an uncorrelated terms. The AAP design was shown to improve the DQE of both material types that have predominantly correlated transfer (such as CsI) and predominantly uncorrelated transfer (such as Se). Improvement in the MTF by 50% and the DQE by 100% at the sampling cut-off frequency is obtained when uncorrelated transfer is prevalent through the converter material. Optimizing high-frequency DQE results in improved image contrast and visualization of small structures and fine-detail.

A sero-survey of rinderpest in nomadic pastoral systems in central and southern Somalia from 2002 to 2003, using a spatially integrated random sampling approach.

PubMed

Tempia, S; Salman, M D; Keefe, T; Morley, P; Freier, J E; DeMartini, J C; Wamwayi, H M; Njeumi, F; Soumaré, B; Abdi, A M

2010-12-01

A cross-sectional sero-survey, using a two-stage cluster sampling design, was conducted between 2002 and 2003 in ten administrative regions of central and southern Somalia, to estimate the seroprevalence and geographic distribution of rinderpest (RP) in the study area, as well as to identify potential risk factors for the observed seroprevalence distribution. The study was also used to test the feasibility of the spatially integrated investigation technique in nomadic and semi-nomadic pastoral systems. In the absence of a systematic list of livestock holdings, the primary sampling units were selected by generating random map coordinates. A total of 9,216 serum samples were collected from cattle aged 12 to 36 months at 562 sampling sites. Two apparent clusters of RP seroprevalence were detected. Four potential risk factors associated with the observed seroprevalence were identified: the mobility of cattle herds, the cattle population density, the proximity of cattle herds to cattle trade routes and cattle herd size. Risk maps were then generated to assist in designing more targeted surveillance strategies. The observed seroprevalence in these areas declined over time. In subsequent years, similar seroprevalence studies in neighbouring areas of Kenya and Ethiopia also showed a very low seroprevalence of RP or the absence of antibodies against RP. The progressive decline in RP antibody prevalence is consistent with virus extinction. Verification of freedom from RP infection in the Somali ecosystem is currently in progress.

Designing a multi-objective, multi-support accuracy assessment of the 2001 National Land Cover Data (NLCD 2001) of the conterminous United States

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Wade, T.G.; Smith, J.H.

2008-01-01

The database design and diverse application of NLCD 2001 pose significant challenges for accuracy assessment because numerous objectives are of interest, including accuracy of land-cover, percent urban imperviousness, percent tree canopy, land-cover composition, and net change. A multi-support approach is needed because these objectives require spatial units of different sizes for reference data collection and analysis. Determining a sampling design that meets the full suite of desirable objectives for the NLCD 2001 accuracy assessment requires reconciling potentially conflicting design features that arise from targeting the different objectives. Multi-stage cluster sampling provides the general structure to achieve a multi-support assessment, and the flexibility to target different objectives at different stages of the design. We describe the implementation of two-stage cluster sampling for the initial phase of the NLCD 2001 assessment, and identify gaps in existing knowledge where research is needed to allow full implementation of a multi-objective, multi-support assessment. ?? 2008 American Society for Photogrammetry and Remote Sensing.

Designing a national soil erosion monitoring network for England and Wales

NASA Astrophysics Data System (ADS)

Lark, Murray; Rawlins, Barry; Anderson, Karen; Evans, Martin; Farrow, Luke; Glendell, Miriam; James, Mike; Rickson, Jane; Quine, Timothy; Quinton, John; Brazier, Richard

2014-05-01

Although soil erosion is recognised as a significant threat to sustainable land use and may be a priority for action in any forthcoming EU Soil Framework Directive, those responsible for setting national policy with respect to erosion are constrained by a lack of robust, representative, data at large spatial scales. This reflects the process-orientated nature of much soil erosion research. Recognising this limitation, The UK Department for Environment, Food and Rural Affairs (Defra) established a project to pilot a cost-effective framework for monitoring of soil erosion in England and Wales (E&W). The pilot will compare different soil erosion monitoring methods at a site scale and provide statistical information for the final design of the full national monitoring network that will: provide unbiased estimates of the spatial mean of soil erosion rate across E&W (tonnes ha-1 yr-1) for each of three land-use classes - arable and horticultural grassland upland and semi-natural habitats quantify the uncertainty of these estimates with confidence intervals. Probability (design-based) sampling provides most efficient unbiased estimates of spatial means. In this study, a 16 hectare area (a square of 400 x 400 m) positioned at the centre of a 1-km grid cell, selected at random from mapped land use across E&W, provided the sampling support for measurement of erosion rates, with at least 94% of the support area corresponding to the target land use classes. Very small or zero erosion rates likely to be encountered at many sites reduce the sampling efficiency and make it difficult to compare different methods of soil erosion monitoring. Therefore, to increase the proportion of samples with larger erosion rates without biasing our estimates, we increased the inclusion probability density in areas where the erosion rate is likely to be large by using stratified random sampling. First, each sampling domain (land use class in E&W) was divided into strata; e.g. two sub-domains within which, respectively, small or no erosion rates, and moderate or larger erosion rates are expected. Each stratum was then sampled independently and at random. The sample density need not be equal in the two strata, but is known and is accounted for in the estimation of the mean and its standard error. To divide the domains into strata we used information on slope angle, previous interpretation of erosion susceptibility of the soil associations that correspond to the soil map of E&W at 1:250 000 (Soil Survey of England and Wales, 1983), and visual interpretation of evidence of erosion from aerial photography. While each domain could be stratified on the basis of the first two criteria, air photo interpretation across the whole country was not feasible. For this reason we used a two-phase random sampling for stratification (TPRS) design (de Gruijter et al., 2006). First, we formed an initial random sample of 1-km grid cells from the target domain. Second, each cell was then allocated to a stratum on the basis of the three criteria. A subset of the selected cells from each stratum were then selected for field survey at random, with a specified sampling density for each stratum so as to increase the proportion of cells where moderate or larger erosion rates were expected. Once measurements of erosion have been made, an estimate of the spatial mean of the erosion rate over the target domain, its standard error and associated uncertainty can be calculated by an expression which accounts for the estimated proportions of the two strata within the initial random sample. de Gruijter, J.J., Brus, D.J., Biekens, M.F.P. & Knotters, M. 2006. Sampling for Natural Resource Monitoring. Springer, Berlin. Soil Survey of England and Wales. 1983 National Soil Map NATMAP Vector 1:250,000. National Soil Research Institute, Cranfield University.

Nonbulk motion system for simultaneously measuring the refractive index and thickness of a sample using tunable optics and spatial signal processing-based Gaussian beam imaging.

PubMed

Reza, Syed Azer; Qasim, Muhammad

2016-01-10

This paper presents a novel approach to simultaneously measuring the thickness and refractive index of a sample. The design uses an electronically controlled tunable lens (ECTL) and a microelectromechanical-system-based digital micromirror device (DMD). The method achieves the desired results by using the DMD to characterize the spatial profile of a Gaussian laser beam at different focal length settings of the ECTL. The ECTL achieves tunable lensing through minimal motion of liquid inside a transparent casing, whereas the DMD contains an array of movable micromirrors, which make it a reflective spatial light modulator. As the proposed system uses an ECTL, a DMD, and other fixed optical components, it measures the thickness and refractive index without requiring any motion of bulk components such as translational and rotational stages. A motion-free system improves measurement repeatability and reliability. Moreover, the measurement of sample thickness and refractive index can be completely automated because the ECTL and DMD are controlled through digital signals. We develop and discuss the theory in detail to explain the measurement methodology of the proposed system and present results from experiments performed to verify the working principle of the method. Refractive index measurement accuracies of 0.22% and 0.2% were achieved for two BK-7 glass samples used, and the thicknesses of the two samples were measured with a 0.1 mm accuracy for each sample, corresponding to a 0.39% and 0.78% measurement error, respectively, for the aforementioned samples.

The Abilities of Understanding Spatial Relations, Spatial Orientation, and Spatial Visualization Affect 3D Product Design Performance: Using Carton Box Design as an Example

ERIC Educational Resources Information Center

Liao, Kun-Hsi

2017-01-01

Three-dimensional (3D) product design is an essential ability that students of subjects related to product design must acquire. The factors that affect designers' performance in 3D design are numerous, one of which is spatial abilities. Studies have reported that spatial abilities can be used to effectively predict people's performance in…

MODIS-Aqua Reveals Evolving Phytoplankton Community Structure During the Arabian Sea Northeast Monsoon

NASA Technical Reports Server (NTRS)

Werdell, P. Jeremy; Roesler, Collin S.; Goes, Joaquim I.

2016-01-01

Applying a bio-optical model designed to identify the mixotrophic dinoflagellate Noctiluca miliaris to MODIS-Aqua revealed (1) patterns in its spatial distribution not previously seen (including its appearance in places not previously sampled), and (2) the surprising disassociation of total chlorophyll biomass with the presence of N. miliaris.

Effects of spatial allocation and parameter variability on lakewide estimates from surveys of Lake Superior, North America’s largest lake

EPA Science Inventory

Lake Superior was sampled in 2011 using a Generalized Random Tessellation Stratified design (n=54 sites) to characterize biological and chemical properties of this huge aquatic resource, with statistical confidence. The lake was divided into two strata (inshore <100m and offsh...

Planning schistosomiasis control: investigation of alternative sampling strategies for Schistosoma mansoni to target mass drug administration of praziquantel in East Africa.

PubMed

Sturrock, Hugh J W; Gething, Pete W; Ashton, Ruth A; Kolaczinski, Jan H; Kabatereine, Narcis B; Brooker, Simon

2011-09-01

In schistosomiasis control, there is a need to geographically target treatment to populations at high risk of morbidity. This paper evaluates alternative sampling strategies for surveys of Schistosoma mansoni to target mass drug administration in Kenya and Ethiopia. Two main designs are considered: lot quality assurance sampling (LQAS) of children from all schools; and a geostatistical design that samples a subset of schools and uses semi-variogram analysis and spatial interpolation to predict prevalence in the remaining unsurveyed schools. Computerized simulations are used to investigate the performance of sampling strategies in correctly classifying schools according to treatment needs and their cost-effectiveness in identifying high prevalence schools. LQAS performs better than geostatistical sampling in correctly classifying schools, but at a cost with a higher cost per high prevalence school correctly classified. It is suggested that the optimal surveying strategy for S. mansoni needs to take into account the goals of the control programme and the financial and drug resources available.

Raster profile development for the spatial data transfer standard

USGS Publications Warehouse

Szemraj, John A.

1993-01-01

The Spatial Data Transfer Standard (SDTS), recently approved as Federal Information Processing Standard (FIPS) Publication 173, is designed to transfer various types of spatial data. Implementing all of the standard's options at one time is impractical. Profiles, or limited subsets of the SDTS, are the mechanisms by which the standards will be implemented. The development of a raster profile is being coordinated by the U.S. Geological Survey's (USGS) SDTS Task Force. This raster profile is intended to accommodate digital georeferenced image data and regularly spaces, georeferenced gridded data. The USGS's digital elevation models (DEMs) and digital orthophoto quadrangles (DOQs), National Oceanic and Atmospheric Administration's (NOAA) advanced very huh resolution radiometer (AVHRR) and Landsat data, and National Aeronautics and Space Administration's (NASA) Earth observing system (EOS) data are among the candidate data sets for this profile. Other raster profiles, designed to support nongeoreferenced and other types of "raw" sensor data will be consider in the future. As with the Topological Vector Profile (TVP) for the SDTS, development of the raster profile includes designing a prototype profile, testing the prototype profile using sample data sets, and finally, requesting and receiving FIPS approval.

A two-phase sampling design for increasing detections of rare species in occupancy surveys

USGS Publications Warehouse

Pacifici, Krishna; Dorazio, Robert M.; Dorazio, Michael J.

2012-01-01

1. Occupancy estimation is a commonly used tool in ecological studies owing to the ease at which data can be collected and the large spatial extent that can be covered. One major obstacle to using an occupancy-based approach is the complications associated with designing and implementing an efficient survey. These logistical challenges become magnified when working with rare species when effort can be wasted in areas with none or very few individuals. 2. Here, we develop a two-phase sampling approach that mitigates these problems by using a design that places more effort in areas with higher predicted probability of occurrence. We compare our new sampling design to traditional single-season occupancy estimation under a range of conditions and population characteristics. We develop an intuitive measure of predictive error to compare the two approaches and use simulations to assess the relative accuracy of each approach. 3. Our two-phase approach exhibited lower predictive error rates compared to the traditional single-season approach in highly spatially correlated environments. The difference was greatest when detection probability was high (0·75) regardless of the habitat or sample size. When the true occupancy rate was below 0·4 (0·05-0·4), we found that allocating 25% of the sample to the first phase resulted in the lowest error rates. 4. In the majority of scenarios, the two-phase approach showed lower error rates compared to the traditional single-season approach suggesting our new approach is fairly robust to a broad range of conditions and design factors and merits use under a wide variety of settings. 5. Synthesis and applications. Conservation and management of rare species are a challenging task facing natural resource managers. It is critical for studies involving rare species to efficiently allocate effort and resources as they are usually of a finite nature. We believe our approach provides a framework for optimal allocation of effort while maximizing the information content of the data in an attempt to provide the highest conservation value per unit of effort.

Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

Zhao, Qing; Royle, Andy; Boomer, G. Scott

2017-01-01

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

Variability of the raindrop size distribution at small spatial scales

NASA Astrophysics Data System (ADS)

Berne, A.; Jaffrain, J.

2010-12-01

Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.

Monitoring survival rates of landbirds at varying spatial scales: An application of the MAPS Program

USGS Publications Warehouse

Rosenberg, D.K.; DeSante, D.F.; Hines, J.E.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

2000-01-01

Survivorship is a primary demographic parameter affecting population dynamics, and thus trends in species abundance. The Monitoring Avian Productivity and Survivorship (MAPS) program is a cooperative effort designed to monitor landbird demographic parameters. A principle goal of MAPS is to estimate annual survivorship and identify spatial patterns and temporal trends in these rates. We evaluated hypotheses of spatial patterns in survival rates among a collection of neighboring sampling sites, such as within national forests, among biogeographic provinces, and between breeding populations that winter in either Central or South America, and compared these geographic-specific models to a model of a common survival rate among all sampling sites. We used data collected during 1992-1995 from Swainson's Thrush (Cathorus ustulatus) populations in the western region of the United States. We evaluated the ability to detect spatial and temporal patterns of survivorship with simulated data. We found weak evidence of spatial differences in survival rates at the local scale of 'location,' which typically contained 3 mist-netting stations. There was little evidence of differences in survival rates among biogeographic provinces or between populations that winter in either Central or South America. When data were pooled for a regional estimate of survivorship, the percent relative bias due to pooling 'locations' was 12 years of monitoring. Detection of spatial patterns and temporal trends in survival rates from local to regional scales will provide important information for management and future research directed toward conservation of landbirds.

Nitrogen Fertilization Elevated Spatial Heterogeneity of Soil Microbial Biomass Carbon and Nitrogen in Switchgrass and Gamagrass Croplands

NASA Astrophysics Data System (ADS)

Jian, S.; Li, J.; Guo, C.; Hui, D.; Deng, Q.; Yu, C. L.; Dzantor, K. E.; Lane, C.

2017-12-01

Nitrogen (N) fertilizers are widely used to increase bioenergy crop yield but intensive fertilizations on spatial distributions of soil microbial processes in bioenergy croplands remains unknown. To quantify N fertilization effect on spatial heterogeneity of soil microbial biomass carbon (MBC) and N (MBN), we sampled top mineral horizon soils (0-15cm) using a spatially explicit design within two 15-m2 plots under three fertilization treatments in two bioenergy croplands in a three-year long fertilization experiment in Middle Tennessee, USA. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha-1 in urea) and high N input (HN: 168 kg N ha-1 in urea). The two crops were switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.). Results showed that N fertilizations little altered central tendencies of microbial variables but relative to LN, HN significantly increased MBC and MBC:MBN (GG only). HN possessed the greatest within-plot variances except for MBN (GG only). Spatial patterns were generally evident under HN and LN plots and much less so under NN plots. Substantially contrasting spatial variations were also identified between croplands (GG>SG) and among variables (MBN, MBC:MBN > MBC). No significant correlations were identified between soil pH and microbial variables. This study demonstrated that spatial heterogeneity is elevated in microbial biomass of fertilized soils likely by uneven fertilizer application, the nature of soil microbial communities and bioenergy crops. Future researchers should better match sample sizes with the heterogeneity of soil microbial property (i.e. MBN) in bioenergy croplands.

Advanced hierarchical distance sampling

USGS Publications Warehouse

Royle, Andy

2016-01-01

In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

Simultaneous measurement of dynamic strain and temperature distribution using high birefringence PANDA fiber Bragg grating

NASA Astrophysics Data System (ADS)

Zhu, Mengshi; Murayama, Hideaki

2017-04-01

New approach in simultaneous measurement of dynamic strain and temperature has been done by using a high birefringence PANDA fiber Bragg grating sensor. By this technique, we have succeeded in discriminating dynamic strain and temperature distribution at the sampling rate of 800 Hz and the spatial resolution of 1 mm. The dynamic distribution of strain and temperature were measured with the deviation of 5mm spatially. In addition, we have designed an experimental setup by which we can apply quantitative dynamic strain and temperature distribution to the fiber under testing without bounding it to a specimen.

Spatial Variability of Soil Water and Soil Organic Carbon Contents Under Different Degradation Degrees of Alpine Meadow Soil over the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zeng, C.; Zhang, F.

2014-12-01

Alpine meadow is one of widespread vegetation types of the Qinghai-Tibetan Plateau. However, alpine meadow ecosystem is undergoing degradation in recent years. The degradation of alpine meadow can changes soil physical and chemical properties as well as it's spatial variability. However, little research has been done that address the spatial patterns of soil properties under different degradation degrees of alpine meadow of the Qinghai-Tibetan Plateau although these changes were important to water and heat study and modelling of land surface. 296 soil surface (0-10 cm) samples were collected using grid sampling design from three different degraded alpine meadow regions (1 km2). Then soil water content (SWC) and organic carbon content (OCC) were measured. Classical statistical and geostatistical methods were employed to study the spatial heterogeneities of SWC and OCC under different degradation degrees (Non-degraded ND, moderately degraded MD, extremely degraded ED) of alpine meadow. Results show that both SWC and OCC of alpine meadow were normally distributed with the exception of SWC under ED. On average, both SWC and OCC of alpine meadow decreased in the order that ND > MD > ED. For nugget ratios, SWC and OCC of alpine meadow showed increasing spatial dependence tendency from ND to ED. For the range of spatial variation, both SWC and OCC of alpine meadow showed increasing tendency in distance with the increasing degree of degradation. In all, the degradation of alpine meadow has significant impact on spatial heterogeneities of SWC and OCC of alpine meadow. With increasing of alpine meadow degradation, soil water condition and nutrient condition become worse, and their distributions in spatial become unevenly.

Flexible detection optics for light scattering

NASA Astrophysics Data System (ADS)

Taratuta, Victor G.; Hurd, Alan J.; Meyer, Robert B.

1984-05-01

We have designed and built a compact, modular apparatus for the collection, viewing, and detection of scattered light for less than 1200, based on a commercially available optical bench. The novelty of our instrument is that it has the flexibility of modular design while allowing the user to see exactly what is happening: both the real image of the sample and the spatial coherence of the scattered light can be examined. There is built-in control over polarization, filtering, magnification, and other parameters.

Linking species richness curves from non-contiguous sampling to contiguous-nested SAR: An empirical study

NASA Astrophysics Data System (ADS)

Lazarina, Maria; Kallimanis, Athanasios S.; Pantis, John D.; Sgardelis, Stefanos P.

2014-11-01

The species-area relationship (SAR) is one of the few generalizations in ecology. However, many different relationships are denoted as SARs. Here, we empirically evaluated the differences between SARs derived from nested-contiguous and non-contiguous sampling designs, using plants, birds and butterflies datasets from Great Britain, Greece, Massachusetts, New York and San Diego. The shape of SAR depends on the sampling scheme, but there is little empirical documentation on the magnitude of the deviation between different types of SARs and the factors affecting it. We implemented a strictly nested sampling design to construct nested-contiguous SAR (SACR), and systematic nested but non-contiguous, and random designs to construct non-contiguous species richness curves (SASRs for systematic and SACs for random designs) per dataset. The SACR lay below any SASR and most of the SACs. The deviation between them was related to the exponent f of the power law relationship between sampled area and extent. The lower the exponent f, the higher was the deviation between the curves. We linked SACR to SASR and SAC through the concept of "effective" area (Ae), i.e. the nested-contiguous area containing equal number of species with the accumulated sampled area (AS) of a non-contiguous sampling. The relationship between effective and sampled area was modeled as log(Ae) = klog(AS). A Generalized Linear Model was used to estimate the values of k from sampling design and dataset properties. The parameter k increased with the average distance between samples and with beta diversity, while k decreased with f. For both systematic and random sampling, the model performed well in predicting effective area in both the training set and in the test set which was totally independent from the training one. Through effective area, we can link different types of species richness curves based on sampling design properties, sampling effort, spatial scale and beta diversity patterns.

Accuracy or precision: Implications of sample design and methodology on abundance estimation

USGS Publications Warehouse

Kowalewski, Lucas K.; Chizinski, Christopher J.; Powell, Larkin A.; Pope, Kevin L.; Pegg, Mark A.

2015-01-01

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Sampling design and procedures for fixed surface-water sites in the Georgia-Florida coastal plain study unit, 1993

USGS Publications Warehouse

Hatzell, H.H.; Oaksford, E.T.; Asbury, C.E.

1995-01-01

The implementation of design guidelines for the National Water-Quality Assessment (NAWQA) Program has resulted in the development of new sampling procedures and the modification of existing procedures commonly used in the Water Resources Division of the U.S. Geological Survey. The Georgia-Florida Coastal Plain (GAFL) study unit began the intensive data collection phase of the program in October 1992. This report documents the implementation of the NAWQA guidelines by describing the sampling design and procedures for collecting surface-water samples in the GAFL study unit in 1993. This documentation is provided for agencies that use water-quality data and for future study units that will be entering the intensive phase of data collection. The sampling design is intended to account for large- and small-scale spatial variations, and temporal variations in water quality for the study area. Nine fixed sites were selected in drainage basins of different sizes and different land-use characteristics located in different land-resource provinces. Each of the nine fixed sites was sampled regularly for a combination of six constituent groups composed of physical and chemical constituents: field measurements, major ions and metals, nutrients, organic carbon, pesticides, and suspended sediments. Some sites were also sampled during high-flow conditions and storm events. Discussion of the sampling procedure is divided into three phases: sample collection, sample splitting, and sample processing. A cone splitter was used to split water samples for the analysis of the sampling constituent groups except organic carbon from approximately nine liters of stream water collected at four fixed sites that were sampled intensively. An example of the sample splitting schemes designed to provide the sample volumes required for each sample constituent group is described in detail. Information about onsite sample processing has been organized into a flowchart that describes a pathway for each of the constituent groups.

Assessing spatial coupling in complex population dynamics using mutual prediction and continuity statistics

USGS Publications Warehouse

Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.

2005-01-01

A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.

Behavior of sensitivities in the one-dimensional advection-dispersion equation: Implications for parameter estimation and sampling design

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1987-01-01

The spatial and temporal variability of sensitivities has a significant impact on parameter estimation and sampling design for studies of solute transport in porous media. Physical insight into the behavior of sensitivities is offered through an analysis of analytically derived sensitivities for the one-dimensional form of the advection-dispersion equation. When parameters are estimated in regression models of one-dimensional transport, the spatial and temporal variability in sensitivities influences variance and covariance of parameter estimates. Several principles account for the observed influence of sensitivities on parameter uncertainty. (1) Information about a physical parameter may be most accurately gained at points in space and time with a high sensitivity to the parameter. (2) As the distance of observation points from the upstream boundary increases, maximum sensitivity to velocity during passage of the solute front increases and the consequent estimate of velocity tends to have lower variance. (3) The frequency of sampling must be “in phase” with the S shape of the dispersion sensitivity curve to yield the most information on dispersion. (4) The sensitivity to the dispersion coefficient is usually at least an order of magnitude less than the sensitivity to velocity. (5) The assumed probability distribution of random error in observations of solute concentration determines the form of the sensitivities. (6) If variance in random error in observations is large, trends in sensitivities of observation points may be obscured by noise and thus have limited value in predicting variance in parameter estimates among designs. (7) Designs that minimize the variance of one parameter may not necessarily minimize the variance of other parameters. (8) The time and space interval over which an observation point is sensitive to a given parameter depends on the actual values of the parameters in the underlying physical system.

A proposal of optimal sampling design using a modularity strategy

NASA Astrophysics Data System (ADS)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Alternative Natural Resource Monitoring Strategies in the Mexican States of Jalisco and Colima

Treesearch

Cele Aguirre-Bravo; Hans Schreuder

2005-01-01

This paper presents a strategy for inventorying and monitoring the natural resources in the Mexican states of Jalisco and Colima. The strategy emphasizes a strong linkage between remote sensing with field sampling design to produce statistical summaries and spatial estimates at multiple scales and resolution levels. Outputs derived from this strategy are expected to...

HIRIS (High-Resolution Imaging Spectrometer: Science opportunities for the 1990s. Earth observing system. Volume 2C: Instrument panel report

NASA Technical Reports Server (NTRS)

1987-01-01

The high-resolution imaging spectrometer (HIRIS) is an Earth Observing System (EOS) sensor developed for high spatial and spectral resolution. It can acquire more information in the 0.4 to 2.5 micrometer spectral region than any other sensor yet envisioned. Its capability for critical sampling at high spatial resolution makes it an ideal complement to the MODIS (moderate-resolution imaging spectrometer) and HMMR (high-resolution multifrequency microwave radiometer), lower resolution sensors designed for repetitive coverage. With HIRIS it is possible to observe transient processes in a multistage remote sensing strategy for Earth observations on a global scale. The objectives, science requirements, and current sensor design of the HIRIS are discussed along with the synergism of the sensor with other EOS instruments and data handling and processing requirements.

MaNGA: Target selection and Optimization

NASA Astrophysics Data System (ADS)

Wake, David

2015-01-01

The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a 'Color-Enhanced' sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

MaNGA: Target selection and Optimization

NASA Astrophysics Data System (ADS)

Wake, David

2016-01-01

The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a "Color-Enhanced" sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

Aberration correction considering curved sample surface shape for non-contact two-photon excitation microscopy with spatial light modulator.

PubMed

Matsumoto, Naoya; Konno, Alu; Inoue, Takashi; Okazaki, Shigetoshi

2018-06-18

In this paper, excitation light wavefront modulation is performed considering the curved sample surface shape to demonstrate high-quality deep observation using two-photon excitation microscopy (TPM) with a dry objective lens. A large spherical aberration typically occurs when the refractive index (RI) interface between air and the sample is a plane perpendicular to the optical axis. Moreover, the curved sample surface shape and the RI mismatch cause various aberrations, including spherical ones. Consequently, the fluorescence intensity and resolution of the obtained image are degraded in the deep regions. To improve them, we designed a pre-distortion wavefront for correcting the aberration caused by the curved sample surface shape by using a novel, simple optical path length difference calculation method. The excitation light wavefront is modulated to the pre-distortion wavefront by a spatial light modulator incorporated in the TPM system before passing through the interface, where the RI mismatch occurs. Thus, the excitation light is condensed without aberrations. Blood vessels were thereby observed up to an optical depth of 2,000 μm in a cleared mouse brain by using a dry objective lens.

Does participation in art classes influence performance on two different cognitive tasks?

PubMed

Schindler, Manuel; Maihöfner, Christian; Bolwerk, Anne; Lang, Frieder R

2017-04-01

Effects of two mentally stimulating art interventions on processing speed and visuo-spatial cognition were compared in three samples. In a randomized 10-week art intervention study with a pre-post follow-up design, 113 adults (27 healthy older adults with subjective memory complaints, 50 healthy older adults and 36 healthy younger adults) were randomly assigned to one of two groups: visual art production or cognitive art evaluation, where the participants either produced or evaluated art. ANOVAs with repeated measures were computed to observe effects on the Symbol-Digit Test, and the Stick Test. Significant Time effects were found with regard to processing speed and visuo-spatial cognition. Additionally, there was found a significant Time × Sample interaction for processing speed. The effects proved robust after testing for education and adding sex as additional factor. Mental stimulation by participation in art classes leads to an improvement of processing speed and visuo-spatial cognition. Further investigation is required to improve understanding of the potential impact of art intervention on cognitive abilities across adulthood.

Enumerative and binomial sampling plans for citrus mealybug (Homoptera: pseudococcidae) in citrus groves.

PubMed

Martínez-Ferrer, María Teresa; Ripollés, José Luís; Garcia-Marí, Ferran

2006-06-01

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

hyperspectral characterization of tissue simulating phantoms using a supercontinuum laser in a spatial frequency domain imaging instrument

NASA Astrophysics Data System (ADS)

Torabzadeh, Mohammad; Stockton, Patrick; Kennedy, Gordon T.; Saager, Rolf B.; Durkin, Anthony J.; Bartels, Randy A.; Tromberg, Bruce J.

2018-02-01

Hyperspectral Imaging (HSI) is a growing field in tissue optics due to its ability to collect continuous spectral features of a sample without a contact probe. Spatial Frequency Domain Imaging (SFDI) is a non-contact wide-field spectral imaging technique that is used to quantitatively characterize tissue structure and chromophore concentration. In this study, we designed a Hyperspectral SFDI (H-SFDI) instrument which integrated a supercontinuum laser source to a wavelength tuning optical configuration and a sCMOS camera to extract spatial (Field of View: 2cm×2cm) and broadband spectral features (580nm-950nm). A preliminary experiment was also performed to integrate the hyperspectral projection unit to a compressed single pixel camera and Light Labeling (LiLa) technique.

Exploring effective sampling design for monitoring soil organic carbon in degraded Tibetan grasslands.

PubMed

Chang, Xiaofeng; Bao, Xiaoying; Wang, Shiping; Zhu, Xiaoxue; Luo, Caiyun; Zhang, Zhenhua; Wilkes, Andreas

2016-05-15

The effects of climate change and human activities on grassland degradation and soil carbon stocks have become a focus of both research and policy. However, lack of research on appropriate sampling design prevents accurate assessment of soil carbon stocks and stock changes at community and regional scales. Here, we conducted an intensive survey with 1196 sampling sites over an area of 190 km(2) of degraded alpine meadow. Compared to lightly degraded meadow, soil organic carbon (SOC) stocks in moderately, heavily and extremely degraded meadow were reduced by 11.0%, 13.5% and 17.9%, respectively. Our field survey sampling design was overly intensive to estimate SOC status with a tolerable uncertainty of 10%. Power analysis showed that the optimal sampling density to achieve the desired accuracy would be 2, 3, 5 and 7 sites per 10 km(2) for lightly, moderately, heavily and extremely degraded meadows, respectively. If a subsequent paired sampling design with the optimum sample size were performed, assuming stock change rates predicted by experimental and modeling results, we estimate that about 5-10 years would be necessary to detect expected trends in SOC in the top 20 cm soil layer. Our results highlight the utility of conducting preliminary surveys to estimate the appropriate sampling density and avoid wasting resources due to over-sampling, and to estimate the sampling interval required to detect an expected sequestration rate. Future studies will be needed to evaluate spatial and temporal patterns of SOC variability. Copyright © 2016. Published by Elsevier Ltd.

Spatial patterns in occupancy and reproduction of Golden Eagles during drought: Prospects for conservation in changing environments

USGS Publications Warehouse

Wiens, David; Kolar, Patrick; Hunt, W. Grainger; Hunt, Teresa; Fuller, Mark R.; Bell, Douglas A.

2018-01-01

We used a broad-scale sampling design to investigate spatial patterns in occupancy and breeding success of territorial pairs of Golden Eagles (Aquila chrysaetos) in the Diablo Range, California, USA, during a period of exceptional drought (2014–2016). We surveyed 138 randomly selected sample sites over 4 occasions each year and identified 199 pairs of eagles, 100 of which were detected in focal sample sites. We then used dynamic multistate modeling to identify relationships between site occupancy and reproduction of Golden Eagles relative to spatial variability in landscape composition and drought conditions. We observed little variability among years in site occupancy (3-yr mean = 0.74), but the estimated annual probability of successful reproduction was relatively low during the study period and declined from 0.39 (± 0.08 SE) to 0.18 (± 0.07 SE). Probabilities of site occupancy and reproduction were substantially greater at sample sites that were occupied by successful breeders in the previous year, indicating the presence of sites that were consistently used by successfully reproducing eagles. We found strong evidence for nonrandom spatial distribution in both occupancy and reproduction: Sites with the greatest potential for occupancy were characterized by rugged terrain conditions with intermediate amounts of grassland interspersed with patches of oak woodland and coniferous forest, whereas successful reproduction was most strongly associated with the amount of precipitation that a site received during the nesting period. Our findings highlight the contribution of consistently occupied and productive breeding sites to overall productivity of the local breeding population, and show that both occupancy and reproduction at these sites were maintained even during a period of exceptional drought. Our approach to quantifying and mapping site quality should be especially useful for the spatial prioritization of compensation measures intended to help offset the impacts of increasing human land use and development on Golden Eagles and their habitats.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Singular value decomposition metrics show limitations of detector design in diffuse fluorescence tomography

PubMed Central

Leblond, Frederic; Tichauer, Kenneth M.; Pogue, Brian W.

2010-01-01

The spatial resolution and recovered contrast of images reconstructed from diffuse fluorescence tomography data are limited by the high scattering properties of light propagation in biological tissue. As a result, the image reconstruction process can be exceedingly vulnerable to inaccurate prior knowledge of tissue optical properties and stochastic noise. In light of these limitations, the optimal source-detector geometry for a fluorescence tomography system is non-trivial, requiring analytical methods to guide design. Analysis of the singular value decomposition of the matrix to be inverted for image reconstruction is one potential approach, providing key quantitative metrics, such as singular image mode spatial resolution and singular data mode frequency as a function of singular mode. In the present study, these metrics are used to analyze the effects of different sources of noise and model errors as related to image quality in the form of spatial resolution and contrast recovery. The image quality is demonstrated to be inherently noise-limited even when detection geometries were increased in complexity to allow maximal tissue sampling, suggesting that detection noise characteristics outweigh detection geometry for achieving optimal reconstructions. PMID:21258566

Design and implementation of estimation-based monitoring programs for flora and fauna: A case study on the Cherokee National Forest

USGS Publications Warehouse

Klimstra, J.D.; O'Connell, A.F.; Pistrang, M.J.; Lewis, L.M.; Herrig, J.A.; Sauer, J.R.

2007-01-01

Science-based monitoring of biological resources is important for a greater understanding of ecological systems and for assessment of the target population using theoretic-based management approaches. When selecting variables to monitor, managers first need to carefully consider their objectives, the geographic and temporal scale at which they will operate, and the effort needed to implement the program. Generally, monitoring can be divided into two categories: index and inferential. Although index monitoring is usually easier to implement, analysis of index data requires strong assumptions about consistency in detection rates over time and space, and parameters are often biasednot accounting for detectability and spatial variation. In most cases, individuals are not always available for detection during sampling periods, and the entire area of interest cannot be sampled. Conversely, inferential monitoring is more rigorous because it is based on nearly unbiased estimators of spatial distribution. Thus, we recommend that detectability and spatial variation be considered for all monitoring programs that intend to make inferences about the target population or the area of interest. Application of these techniques is especially important for the monitoring of Threatened and Endangered (T&E) species because it is critical to determine if population size is increasing or decreasing with some level of certainty. Use of estimation-based methods and probability sampling will reduce many of the biases inherently associated with index data and provide meaningful information with respect to changes that occur in target populations. We incorporated inferential monitoring into protocols for T&E species spanning a wide range of taxa on the Cherokee National Forest in the Southern Appalachian Mountains. We review the various approaches employed for different taxa and discuss design issues, sampling strategies, data analysis, and the details of estimating detectability using site occupancy. These techniques provide a science-based approach for monitoring and can be of value to all resource managers responsible for management of T&E species.

A preliminary assessment of the spatial sources of contemporary suspended sediment in the Ohio River basin, United States, using water quality data from the NASQAN programme in a source tracing procedure

USGS Publications Warehouse

Zhang, Y.-S.; Collins, A.L.; Horowitz, A.J.

2012-01-01

Reliable information on catchment scale suspended sediment sources is required to inform the design of management strategies for helping abate the numerous environmental issues associated with enhanced sediment mobilization and off-site loadings. Since sediment fingerprinting techniques avoid many of the logistical constraints associated with using more traditional indirect measurement methods at catchment scale, such approaches have been increasingly reported in the international literature and typically use data sets collected specifically for sediment source apportionment purposes. There remains scope for investigating the potential for using geochemical data sets assembled by routine monitoring programmes to fingerprint sediment provenance. In the United States, routine water quality samples are collected as part of the US Geological Survey's revised National Stream Quality Accounting Network programme. Accordingly, the geochemistry data generated from these samples over a 10-year period (1996-2006) were used as the basis for a fingerprinting exercise to assess the key tributary sub-catchment spatial sources of contemporary suspended sediment transported by the Ohio River. Uncertainty associated with the spatial source estimates was quantified using a Monte Carlo approach in conjunction with mass balance modelling. Relative frequency weighted means were used as an alternative way of summarizing the spatial source contributions, thereby avoiding the need to use confidence limits. The results should be interpreted in the context of the routine, but infrequent nature, of the suspended sediment samples used to assemble geochemistry as a basis for the sourcing exercise. Nonetheless, the study demonstrates how routine monitoring samples can be used to provide some preliminary information on sediment provenance in large drainage basins. ?? 2011 John Wiley & Sons, Ltd.

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

NASA Technical Reports Server (NTRS)

Bingham, G. E.; Cantwell, G.; Robinson, R. C.; Revercomb, H. E.; Smith, W. L.

2001-01-01

A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.

Dryland soil microbial communities display spatial biogeographic patterns associated with soil depth and soil parent material

USGS Publications Warehouse

Steven, Blaire; Gallegos-Graves, La Verne; Belnap, Jayne; Kuske, Cheryl R.

2013-01-01

Biological soil crusts (biocrusts) are common to drylands worldwide. We employed replicated, spatially nested sampling and 16S rRNA gene sequencing to describe the soil microbial communities in three soils derived from different parent material (sandstone, shale, and gypsum). For each soil type, two depths (biocrusts, 0–1 cm; below-crust soils, 2–5 cm) and two horizontal spatial scales (15 cm and 5 m) were sampled. In all three soils, Cyanobacteria and Proteobacteria demonstrated significantly higher relative abundance in the biocrusts, while Chloroflexi and Archaea were significantly enriched in the below-crust soils. Biomass and diversity of the communities in biocrusts or below-crust soils did not differ with soil type. However, biocrusts on gypsum soil harbored significantly larger populations of Actinobacteria and Proteobacteria and lower populations of Cyanobacteria. Numerically dominant operational taxonomic units (OTU; 97% sequence identity) in the biocrusts were conserved across the soil types, whereas two dominant OTUs in the below-crust sand and shale soils were not identified in the gypsum soil. The uniformity with which small-scale vertical community differences are maintained across larger horizontal spatial scales and soil types is a feature of dryland ecosystems that should be considered when designing management plans and determining the response of biocrusts to environmental disturbances.

Design of a WSN for the Sampling of Environmental Variability in Complex Terrain

PubMed Central

Martín-Tardío, Miguel A.; Felicísimo, Ángel M.

2014-01-01

In-situ environmental parameter measurements using sensor systems connected to a wireless network have become widespread, but the problem of monitoring large and mountainous areas by means of a wireless sensor network (WSN) is not well resolved. The main reasons for this are: (1) the environmental variability distribution is unknown in the field; (2) without this knowledge, a huge number of sensors would be necessary to ensure the complete coverage of the environmental variability and (3) WSN design requirements, for example, effective connectivity (intervisibility), limiting distances and controlled redundancy, are usually solved by trial and error. Using temperature as the target environmental variable, we propose: (1) a method to determine the homogeneous environmental classes to be sampled using the digital elevation model (DEM) and geometric simulations and (2) a procedure to determine an effective WSN design in complex terrain in terms of the number of sensors, redundancy, cost and spatial distribution. The proposed methodology, based on geographic information systems and binary integer programming can be easily adapted to a wide range of applications that need exhaustive and continuous environmental monitoring with high spatial resolution. The results show that the WSN design is perfectly suited to the topography and the technical specifications of the sensors, and provides a complete coverage of the environmental variability in terms of Sun exposure. However these results still need be validated in the field and the proposed procedure must be refined. PMID:25412218

A spatially resolved retarding field energy analyzer design suitable for uniformity analysis across the surface of a semiconductor wafer

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

Sharma, S., E-mail: shailesh.sharma6@mail.dcu.ie; National Centre for Plasma Science and Technology, Dublin City University, Glasnevin, Dublin 9; Gahan, D., E-mail: david.gahan@impedans.com

2014-04-15

A novel retarding field energy analyzer design capable of measuring the spatial uniformity of the ion energy and ion flux across the surface of a semiconductor wafer is presented. The design consists of 13 individual, compact-sized, analyzers, all of which are multiplexed and controlled by a single acquisition unit. The analyzers were tested to have less than 2% variability from unit to unit due to tight manufacturing tolerances. The main sensor assembly consists of a 300 mm disk to mimic a semiconductor wafer and the plasma sampling orifices of each sensor are flush with disk surface. This device is placedmore » directly on top of the rf biased electrode, at the wafer location, in an industrial capacitively coupled plasma reactor without the need for any modification to the electrode structure. The ion energy distribution, average ion energy, and average ion flux were measured at the 13 locations over the surface of the powered electrode to determine the degree of spatial nonuniformity. The ion energy and ion flux are shown to vary by approximately 20% and 5%, respectively, across the surface of the electrode for the range of conditions investigated in this study.« less

Effects of Spatial Experiences & Cognitive Styles in the Solution Process of Space-Based Design Problems in the First Year of Architectural Design Education

ERIC Educational Resources Information Center

Erkan Yazici, Yasemin

2013-01-01

There are many factors that influence designers in the architectural design process. Cognitive style, which varies according to the cognitive structure of persons, and spatial experience, which is created with spatial data acquired during life are two of these factors. Designers usually refer to their spatial experiences in order to find solutions…

Characterization of spatial distribution of Tetranychus urticae in peppermint in California and implication for improving sampling plan.

PubMed

Rijal, Jhalendra P; Wilson, Rob; Godfrey, Larry D

2016-02-01

Twospotted spider mite, Tetranychus urticae Koch, is an important pest of peppermint in California, USA. Spider mite feeding on peppermint leaves causes physiological changes in the plant, which coupling with the favorable environmental condition can lead to increased mite infestations. Significant yield loss can occur in absence of pest monitoring and timely management. Understating the within-field spatial distribution of T. urticae is critical for the development of reliable sampling plan. The study reported here aims to characterize the spatial distribution of mite infestation in four commercial peppermint fields in northern California using spatial techniques, variogram and Spatial Analysis by Distance IndicEs (SADIE). Variogram analysis revealed that there was a strong evidence for spatially dependent (aggregated) mite population in 13 of 17 sampling dates and the physical distance of the aggregation reached maximum to 7 m in peppermint fields. Using SADIE, 11 of 17 sampling dates showed aggregated distribution pattern of mite infestation. Combining results from variogram and SADIE analysis, the spatial aggregation of T. urticae was evident in all four fields for all 17 sampling dates evaluated. Comparing spatial association using SADIE, ca. 62% of the total sampling pairs showed a positive association of mite spatial distribution patterns between two consecutive sampling dates, which indicates a strong spatial and temporal stability of mite infestation in peppermint fields. These results are discussed in relation to behavior of spider mite distribution within field, and its implications for improving sampling guidelines that are essential for effective pest monitoring and management.

Characterization of the LANDSAT sensors' spatial responses

NASA Technical Reports Server (NTRS)

Markham, B. L.

1984-01-01

The characteristics of the thematic mapper (TM) and multispectral scanner (MSS) sensors on LANDSATs 4 and 5 affecting their spatial responses are described, and functions defining the response of the system to an arbitrary input spatial pattern are derived, i.e., transfer functions (TF) and line spread functions (LSF). These design LSF's and TF's were modified based on prelaunch component and system measurements to provide improved estimates. Prelaunch estimates of LSF/FT's are compared to in-orbit estimates. For the MSS instruments, only limited prelaunch scan direction square-wave response (SWR) data were available. Design estimates were modified by convolving in Gaussian blur till the derived LSF/TF's produced SWR's comparable to the measurements. The two MSS instruments were comparable at their temperatures of best focus; separate calculations were performed for bands 1 and 3, band 2 and band 4. The pre-sample nadir effective instantaneous field's of view (EIFOV's) based on the .5 modulation transfer function (MTF) criteria vary from 70 to 75 meters in the track direction and 79 to 82 meters in the scan direction. For the TM instruments more extensive prelaunch measurements were available. Bands 1 to 4, 5 and 7, and 6 were handled separately as were the two instruments. Derived MTF's indicate nadir pre-sample EIFOV's of 32 to 33 meter track (bands 1 to 5, 7) and 36 meter scan (bands 1 to 5, 7) and 1245 meter track (band 6) and 141 meter scan (band 6) for both TM's.

CentNet—A deployable 100-station network for surface exchange research

NASA Astrophysics Data System (ADS)

Oncley, S.; Horst, T. W.; Semmer, S.; Militzer, J.; Maclean, G.; Knudson, K.

2014-12-01

Climate, air quality, atmospheric composition, surface hydrology, and ecological processes are directly affected by the Earth's surface. Complexity of this surface exists at multiple spatial scales, which complicates the understanding of these processes. NCAR/EOL currently provides a facility to the research community to make direct eddy-covariance flux observations to quantify surface-atmosphere interactions. However, just as model resolution has continued to increase, there is a need to increase the spatial density of flux measurements to capture the wide variety of scales that contribute to exchange processes close to the surface. NCAR/EOL now has developed the CentNet facility, that is envisioned to have on the order of 100 surface flux stations deployable for periods of months to years. Each station would measure standard meteorological variables, all components of the surface energy balance (including turbulence fluxes and radiation), atmospheric composition, and other quantities to characterize the surface. Thus, CentNet can support observational research in the biogeosciences, hydrology, urban meteorology, basic meteorology, and turbulence. CentNet has been designed to be adaptable to a wide variety of research problems while keeping operations manageable. Tower infrastructure has been designed to be lightweight, easily deployed, and with a minimal set-up footprint. CentNet uses sensor networks to increase spatial sampling at each station. The data system saves every sample on site to retain flexibility in data analysis. We welcome guidance on development and funding priorities as we build CentNet.

Association of gender and specialty interest with video-gaming, three-dimensional spatial analysis, and entry-level laparoscopic skills in third-year veterinary students.

PubMed

Bragg, Heather R; Towle Millard, Heather A; Millard, Ralph P; Constable, Peter D; Freeman, Lyn J

2016-06-15

OBJECTIVE To determine whether gender or interest in pursuing specialty certification in internal medicine or surgery was associated with video-gaming, 3-D spatial analysis, or entry-level laparoscopic skills in third-year veterinary students. DESIGN Cross-sectional study. SAMPLE A convenience sample of 68 (42 female and 26 male) third-year veterinary students. PROCEDURES Participants completed a survey asking about their interest in pursuing specialty certification in internal medicine or surgery. Subsequently, participants' entry-level laparoscopic skills were assessed with 3 procedures performed in box trainers, their video-gaming skills were tested with 3 video games, and their 3-D spatial analysis skills were evaluated with the Purdue University Visualization of Rotations Spatial Test. Scores were assigned for laparoscopic, video-gaming, and 3-D spatial analysis skills. RESULTS Significantly more female than male students were interested in pursuing specialty certification in internal medicine (23/42 vs 7/26), and significantly more male than female students were interested in pursuing specialty certification in surgery (19/26 vs 19/42). Males had significantly higher video-gaming skills scores than did females, but spatial analysis and laparoscopic skills scores did not differ between males and females. Students interested in pursuing specialty certification in surgery had higher video-gaming and spatial analysis skills scores than did students interested in pursuing specialty certification in internal medicine, but laparoscopic skills scores did not differ between these 2 groups. CONCLUSIONS AND CLINICAL RELEVANCE For this group of students, neither gender nor interest in specialty certification in internal medicine versus surgery was associated with entry-level laparoscopy skills.

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Modeling the impacts of phenological and inter-annual changes in landscape metrics on local biodiversity of agricultural lands of Eastern Ontario using multi-spatial and multi-temporal remote sensing data

NASA Astrophysics Data System (ADS)

Alavi-Shoushtari, N.; King, D.

2017-12-01

Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of season date across the sample landscapes and the variability in the corresponding NDVI values at that date showed the strongest correlation with the biodiversity indices; 3) The significance of the models improved when using 3×3km site extent both for MODIS and Landsat based models due most likely to the larger sample size over 3x3km.

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.

Patterns in Temporal Variability of Temperature, Oxygen and pH along an Environmental Gradient in a Coral Reef

PubMed Central

Guadayol, Òscar; Silbiger, Nyssa J.; Donahue, Megan J.; Thomas, Florence I. M.

2014-01-01

Spatial and temporal environmental variability are important drivers of ecological processes at all scales. As new tools allow the in situ exploration of individual responses to fluctuations, ecologically meaningful ways of characterizing environmental variability at organism scales are needed. We investigated the fine-scale spatial heterogeneity of high-frequency temporal variability in temperature, dissolved oxygen concentration, and pH experienced by benthic organisms in a shallow coastal coral reef. We used a spatio-temporal sampling design, consisting of 21 short-term time-series located along a reef flat-to-reef slope transect, coupled to a long-term station monitoring water column changes. Spectral analyses revealed sharp gradients in variance decomposed by frequency, as well as differences between physically-driven and biologically-reactive parameters. These results highlight the importance of environmental variance at organismal scales and present a new sampling scheme for exploring this variability in situ. PMID:24416364

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

USGS Publications Warehouse

Vierling, L.A.; Fersdahl, M.; Chen, X.; Li, Z.; Zimmerman, P.

2006-01-01

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Feasibility of conducting wetfall chemistry investigations around the Bowen Power Plant

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

Chen, N.C.J.; Patrinos, A.A.N.

1979-10-01

The feasibility of expanding the Meteorological Effects of Thermal Energy Releases - Oak Ridge National Laboratory (METER-ORNL) research at Bower Power Plant, a coal-fired power plant in northwest Georgia, to include wetfall chemistry is evaluated using results of similar studies around other power plants, several atmospheric washout models, analysis of spatial variability in precipitation, and field logistical considerations. An optimal wetfall chemistry network design is proposed, incorporating the inner portion of the existing rain-gauge network and augmented by additional sites to ensure adequate coverage of probable target areas. The predicted sulfate production rate differs by about four orders of magnitudemore » among the models reviewed with a pH of 3. No model can claim superiority over any other model without substantive data verification. The spatial uniformity in rain amount is evaluated using four storms that occurred at the METER-ORNL network. Values of spatial variability ranged from 8 to 31% and decreased as the mean rainfall increased. The field study of wetfall chemistry will require a minimum of 5 persons to operate the approximately 50 collectors covering an area of 740 km/sup 2/. Preliminary wetfall-only samples collected on an event basis showed lower pH and higher electrical conductivity of precipitation collected about 5 km downwind of the power plant relative to samples collected upwind. Wetfall samples collected on a weekly basis using automatic samplers, however, showed variable results, with no consistent pattern. This suggests the need for event sampling to minimize variable rain volume and multiple-source effects often associated with weekly samples.« less

Application of laser scanning speckle-microscopy for high-resolution express diagnostics of chlamydial infection

NASA Astrophysics Data System (ADS)

Ulyanov, Sergey; Larionova, Olga; Ulianova, Onega; Zaitsev, Sergey; Saltykov, Yury; Polyanina, Tatiana; Lyapina, Anna; Filonova, Nadezhda; Subbotina, Irina; Kalduzova, Irina; Utz, Sergey; Moiseeva, Yulia; Feodorova, Valentina

2018-04-01

Method of speckle-microscopy has been adapted to the problem of detection of Chlamydia trachomatis microbial cells in clinical samples. Prototype of laser scanning speckle-microscope has been designed. Spatial resolution and output characteristics of this microscope have been analyzed for the case of scanning of C. trachomatis bacteria inclusions - Elementary Bodies (EBs) inside the human cells, fixed on the glass. It has been demonstrated, that presence of C. trachomatis microbial cells in the sample can be easily detected using speckle microscopy.

MRI and unilateral NMR study of reindeer skin tanning processes.

PubMed

Zhu, Lizheng; Del Federico, Eleonora; Ilott, Andrew J; Klokkernes, Torunn; Kehlet, Cindie; Jerschow, Alexej

2015-04-07

The study of arctic or subarctic indigenous skin clothing material, known for its design and ability to keep the body warm, provides information about the tanning materials and techniques. The study also provides clues about the culture that created it, since tanning processes are often specific to certain indigenous groups. Untreated skin samples and samples treated with willow (Salix sp) bark extract and cod liver oil are compared in this study using both MRI and unilateral NMR techniques. The two types of samples show different proton spatial distributions and different relaxation times, which may also provide information about the tanning technique and aging behavior.

The resolution capability of an irregularly sampled dataset: With application to Geosat altimeter data

NASA Technical Reports Server (NTRS)

Chelton, Dudley B.; Schlax, Michael G.

1994-01-01

A formalism is presented for determining the wavenumber-frequency transfer function associated with an irregularly sampled multidimensional dataset. This transfer function reveals the filtering characteristics and aliasing patterns inherent in the sample design. In combination with information about the spectral characteristics of the signal, the transfer function can be used to quantify the spatial and temporal resolution capability of the dataset. Application of the method to idealized Geosat altimeter data (i.e., neglecting measurement errors and data dropouts) concludes that the Geosat orbit configuration is capable of resolving scales of about 3 deg in latitude and longitude by about 30 days.

Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field

PubMed Central

Petrovskaya, Natalia B.; Forbes, Emily; Petrovskii, Sergei V.; Walters, Keith F. A.

2018-01-01

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid. PMID:29495513

Interception loss, throughfall and stemflow in a maritime pine stand. I. Variability of throughfall and stemflow beneath the pine canopy

NASA Astrophysics Data System (ADS)

Loustau, D.; Berbigier, P.; Granier, A.; Moussa, F. El Hadj

1992-10-01

Patterns of spatial variability of throughfall and stemflow were determined in a maritime pine ( Pinus pinaster Ait.) stand for two consecutive years. Data were obtained from 52 fixed rain gauges and 12 stemflow measuring devices located in a 50m × 50m plot at the centre of an 18-year-old stand. The pine trees had been sown in rows 4m apart and had reached an average height of 12.6m. The spatial distribution of stems had a negligible effect on the throughfall partitioning beneath the canopy. Variograms of throughfall computed for a sample of storms did not reveal any spatial autocorrelation of throughfall for the sampling design used. Differences in throughfall, in relation to the distance from the rows, were not consistently significant. In addition, the distance from the tree stem did not influence the amount of throughfall. The confidence interval on the amount of throughfall per storm was between 3 and 8%. The stemflow was highly variable between trees. The effect of individual trees on stemflow was significant but the amount of stemflow per tree was not related to tree size (i.e. height, trunk diameter, etc.). The cumulative sampling errors on stemflow and throughfall for a single storm created a confidence interval of between ±7 and ±51% on interception. This resulted mainly from the low interception rate and sampling error on throughfall.

A Japanese New Altimetry Mission, COMPIRA - Towards High Temporal and Spatial Sampling of Sea Surface Height Measurement

NASA Astrophysics Data System (ADS)

Ito, N.; Uematsu, A.; Yajima, Y.; Isoguchi, O.

2014-12-01

Japan Aerospace Exploration Agency (JAXA) is working on a conceptual study of altimeter mission named Coastal and Ocean measurement Mission with Precise and Innovative Radar Altimeter (COMPIRA), which will carry a wide-swath altimeter named Synthetic aperture radar (SAR) Height Imaging Oceanic Sensor with Advanced Interferometry (SHIOSAI). Capturing meso/submeso-scale phenomena is one of important objectives of the COMPIRA mission, as well as operational oceanography and fishery. For operational oceanography including coastal forecast, swath of SHIOSAI is selected to be 80 km in left and right sides to maximize temporal and spatial sampling of the sea surface height. Orbit specifications are also designed to be better sampling especially for mid-latitude region. That is, a spatial grid sampling is 5 km and an observation times per revisit period (about 10 days) is 2 to 3 times. In order to meet both sampling frequency and spatial coverage requirements as much as possible, orbit inclination was set relatively low, 51 degrees. Although this sampling frequency is, of course, not enough high to capture time evolution of coastal phenomena, an assimilation process would compensate its time evolution if 2D SSH fields was observed at least once within decal time scale of phenomena. JAXA has launched a framework called "Coastal forecast core team" to aim at developing coastal forecast system through pre-launch activities toward COMPIRA. Assimilation segment as well as satellite and in situ data provision will play an important role on these activities. As a first step, we evaluated effects of ocean current forecast improvement with COMPIRA-simulated wide-swath and high sampling sea surface heights (SSH) data. Simulated SSH data are generated from regional ocean numerical models and the COMPIRA orbit and error specifications. Then, identical twin experiments are conducted to investigate the effect of wide-swath SSH measurements on coastal forecast in the Tohoku Pacific coast region. The experiment shows that simulated sea surface current using COMPIRA data as an input data for assimilation well represents vortical feature, which cannot be reproduced by conventional nadir altimeters.

High-speed spatial scanning pyrometer

NASA Technical Reports Server (NTRS)

Cezairliyan, A.; Chang, R. F.; Foley, G. M.; Miller, A. P.

1993-01-01

A high-speed spatial scanning pyrometer has been designed and developed to measure spectral radiance temperatures at multiple target points along the length of a rapidly heating/cooling specimen in dynamic thermophysical experiments at high temperatures (above about 1800 K). The design, which is based on a self-scanning linear silicon array containing 1024 elements, enables the pyrometer to measure spectral radiance temperatures (nominally at 650 nm) at 1024 equally spaced points along a 25-mm target length. The elements of the array are sampled consecutively every 1 microsec, thereby permitting one cycle of measurements to be completed in approximately 1 msec. Procedures for calibration and temperature measurement as well as the characteristics and performance of the pyrometer are described. The details of sources and estimated magnitudes of possible errors are given. An example of measurements of radiance temperatures along the length of a tungsten rod, during its cooling following rapid resistive pulse heating, is presented.

Design of titania nanotube structures by focused laser beam direct writing

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

Enachi, Mihai; Stevens-Kalceff, Marion A.; Sarua, Andrei

In this work, we report on electrochemical fabrication of titania films consisting of nanotubes (NTs) and their treatment by focused laser beam. The results of sample characterization by optical and scanning electron microscopy, cathodoluminescence imaging, and Raman scattering scanning spectroscopy are compared to those inherent to specimens subjected to thermal treatment in a furnace. The obtained data demonstrate possibilities for controlling crystallographic structure of TiO{sub 2} NTs by focused laser beam direct writing. These findings open new prospects for the design and fabrication of spatial architectures based on titania nanotubes.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

PubMed

Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures.

A sampling design framework for monitoring secretive marshbirds

USGS Publications Warehouse

Johnson, D.H.; Gibbs, J.P.; Herzog, M.; Lor, S.; Niemuth, N.D.; Ribic, C.A.; Seamans, M.; Shaffer, T.L.; Shriver, W.G.; Stehman, S.V.; Thompson, W.L.

2009-01-01

A framework for a sampling plan for monitoring marshbird populations in the contiguous 48 states is proposed here. The sampling universe is the breeding habitat (i.e. wetlands) potentially used by marshbirds. Selection protocols would be implemented within each of large geographical strata, such as Bird Conservation Regions. Site selection will be done using a two-stage cluster sample. Primary sampling units (PSUs) would be land areas, such as legal townships, and would be selected by a procedure such as systematic sampling. Secondary sampling units (SSUs) will be wetlands or portions of wetlands in the PSUs. SSUs will be selected by a randomized spatially balanced procedure. For analysis, the use of a variety of methods as a means of increasing confidence in conclusions that may be reached is encouraged. Additional effort will be required to work out details and implement the plan.

Micromega/IR: Design and status of a near-infrared spectral microscope for in situ analysis of Mars samples

NASA Astrophysics Data System (ADS)

Leroi, Vaitua; Bibring, Jean-Pierre; Berthe, Michel

2009-07-01

MicrOmega is an ultra miniaturized spectral microscope for in situ analysis of samples. It is composed of 2 microscopes; one with a spatial sampling less or equal to 4 μm, working in 4 colors in the visible range: MicrOmega/VIS, and a NIR hyperspectral microscope working in the spectral range 0.9-4 μm with a spatial sampling of 20 μm per pixel: MicrOmega/IR (described in this paper). MicrOmega/IR illuminates and images samples a few mm in size and acquires the NIR spectrum of each resolved pixel in up to 320 contiguous spectral channels. The goal of this instrument is to analyze in situ the composition of collected samples at almost their grain size scale, in a non-destructive way. With the chosen spectral range and resolution, a wide variety of constituents can be identified: minerals, such as pyroxene and olivine, ferric oxides, hydrated phyllosilicates, sulfates and carbonates and ices and organics. The composition of the various phases within a given sample is a critical record of its formation and evolution. Coupled to the mapping information, it provides unique clues to describe the history of the parent body (planet, satellite and small body). In particular, the capability to identify hydrated grains and to characterize their adjacent phases has a huge potential in the search for possible bio-relics.

Influence of Design Training and Spatial Solution Strategies on Spatial Ability Performance

ERIC Educational Resources Information Center

Lin, Hanyu

2016-01-01

Numerous studies have reported that spatial ability improves through training. This study investigated the following: (1) whether design training enhances spatial ability and (2) whether differing solution strategies are applied or generated following design training. On the basis of these two research objectives, this study divided the…

Novel lineage patterns from an automated water sampler to probe marine microbial biodiversity with ships of opportunity

NASA Astrophysics Data System (ADS)

Stern, Rowena F.; Picard, Kathryn T.; Hamilton, Kristina M.; Walne, Antony; Tarran, Glen A.; Mills, David; McQuatters-Gollop, Abigail; Edwards, Martin

2015-09-01

There is a paucity of data on long-term, spatially resolved changes in microbial diversity and biogeography in marine systems, and yet these organisms underpin fundamental ecological processes in the oceans affecting socio-economic values of the marine environment. We report results from a new autonomous Water and Microplankton Sampler (WaMS) that is carried within the Continuous Plankton Recorder (CPR). Whilst the CPR with its larger mesh size (270 μm), is designed to capture larger plankton, the WaMS was designed as an additional device to capture plankton below 50 μm and delicate larger species, often destroyed by net sampling methods. A 454 pyrosequencing and flow cytometric investigation of eukaryotic microbes using the partial 18S rDNA from thirteen WaMS samples collected over three months in the English Channel revealed a wide diversity of organisms. Alveolates, Fungi, and picoplanktonic Chlorophytes were the most common lineages captured despite the small sample volumes (200-250 ml). The survey also identified Cercozoa and MAST heterotrophic Stramenopiles, normally missed in microscopic-based plankton surveys. The most common was the likely parasitic LKM11 Rozellomycota lineage which comprised 43.2% of all reads and are rarely observed in marine pelagic surveys. An additional 9.5% of reads belonged to other parasitic lineages including marine Syndiniales and Ichthyosporea. Sample variation was considerable, indicating that microbial diversity is spatially or temporally patchy. Our study has shown that the WaMS sampling system is autonomous, versatile and robust, and due to its deployment on the established CPR network, is a cost-effective monitoring tool for microbial diversity for the detection of smaller and delicate taxa.

Impacts of sampling design and estimation methods on nutrient leaching of intensively monitored forest plots in the Netherlands.

PubMed

de Vries, W; Wieggers, H J J; Brus, D J

2010-08-05

Element fluxes through forest ecosystems are generally based on measurements of concentrations in soil solution at regular time intervals at plot locations sampled in a regular grid. Here we present spatially averaged annual element leaching fluxes in three Dutch forest monitoring plots using a new sampling strategy in which both sampling locations and sampling times are selected by probability sampling. Locations were selected by stratified random sampling with compact geographical blocks of equal surface area as strata. In each sampling round, six composite soil solution samples were collected, consisting of five aliquots, one per stratum. The plot-mean concentration was estimated by linear regression, so that the bias due to one or more strata being not represented in the composite samples is eliminated. The sampling times were selected in such a way that the cumulative precipitation surplus of the time interval between two consecutive sampling times was constant, using an estimated precipitation surplus averaged over the past 30 years. The spatially averaged annual leaching flux was estimated by using the modeled daily water flux as an ancillary variable. An important advantage of the new method is that the uncertainty in the estimated annual leaching fluxes due to spatial and temporal variation and resulting sampling errors can be quantified. Results of this new method were compared with the reference approach in which daily leaching fluxes were calculated by multiplying daily interpolated element concentrations with daily water fluxes and then aggregated to a year. Results show that the annual fluxes calculated with the reference method for the period 2003-2005, including all plots, elements and depths, lies only in 53% of the cases within the range of the average +/-2 times the standard error of the new method. Despite the differences in results, both methods indicate comparable N retention and strong Al mobilization in all plots, with Al leaching being nearly equal to the leaching of SO(4) and NO(3) with fluxes expressed in mol(c) ha(-1) yr(-1). This illustrates that Al release, which is the clearest signal of soil acidification, is mainly due to the external input of SO(4) and NO(3).

Low spatial coherence electrically pumped semiconductor laser for speckle-free full-field imaging

PubMed Central

Redding, Brandon; Cerjan, Alexander; Huang, Xue; Lee, Minjoo Larry; Stone, A. Douglas; Choma, Michael A.; Cao, Hui

2015-01-01

The spatial coherence of laser sources has limited their application to parallel imaging and projection due to coherent artifacts, such as speckle. In contrast, traditional incoherent light sources, such as thermal sources or light emitting diodes (LEDs), provide relatively low power per independent spatial mode. Here, we present a chip-scale, electrically pumped semiconductor laser based on a novel design, demonstrating high power per mode with much lower spatial coherence than conventional laser sources. The laser resonator was fabricated with a chaotic, D-shaped cavity optimized to achieve highly multimode lasing. Lasing occurs simultaneously and independently in ∼1,000 modes, and hence the total emission exhibits very low spatial coherence. Speckle-free full-field imaging is demonstrated using the chaotic cavity laser as the illumination source. The power per mode of the sample illumination is several orders of magnitude higher than that of a LED or thermal light source. Such a compact, low-cost source, which combines the low spatial coherence of a LED with the high spectral radiance of a laser, could enable a wide range of high-speed, full-field imaging and projection applications. PMID:25605946

Low spatial coherence electrically pumped semiconductor laser for speckle-free full-field imaging.

PubMed

Redding, Brandon; Cerjan, Alexander; Huang, Xue; Lee, Minjoo Larry; Stone, A Douglas; Choma, Michael A; Cao, Hui

2015-02-03

The spatial coherence of laser sources has limited their application to parallel imaging and projection due to coherent artifacts, such as speckle. In contrast, traditional incoherent light sources, such as thermal sources or light emitting diodes (LEDs), provide relatively low power per independent spatial mode. Here, we present a chip-scale, electrically pumped semiconductor laser based on a novel design, demonstrating high power per mode with much lower spatial coherence than conventional laser sources. The laser resonator was fabricated with a chaotic, D-shaped cavity optimized to achieve highly multimode lasing. Lasing occurs simultaneously and independently in ∼1,000 modes, and hence the total emission exhibits very low spatial coherence. Speckle-free full-field imaging is demonstrated using the chaotic cavity laser as the illumination source. The power per mode of the sample illumination is several orders of magnitude higher than that of a LED or thermal light source. Such a compact, low-cost source, which combines the low spatial coherence of a LED with the high spectral radiance of a laser, could enable a wide range of high-speed, full-field imaging and projection applications.

Young Stellar Populations in MYStIX Star-forming Regions: Candidate Protostars

NASA Astrophysics Data System (ADS)

Romine, Gregory; Feigelson, Eric D.; Getman, Konstantin V.; Kuhn, Michael A.; Povich, Matthew S.

2016-12-01

The Massive Young Star-Forming Complex in Infrared and X-ray (MYStIX) project provides a new census on stellar members of massive star-forming regions within 4 kpc. Here the MYStIX Infrared Excess catalog and Chandra-based X-ray photometric catalogs are mined to obtain high-quality samples of Class I protostars using criteria designed to reduce extragalactic and Galactic field star contamination. A total of 1109 MYStIX Candidate Protostars (MCPs) are found in 14 star-forming regions. Most are selected from protoplanetary disk infrared excess emission, but 20% are found from their ultrahard X-ray spectra from heavily absorbed magnetospheric flare emission. Two-thirds of the MCP sample is newly reported here. The resulting samples are strongly spatially associated with molecular cores and filaments on Herschel far-infrared maps. This spatial agreement and other evidence indicate that the MCP sample has high reliability with relatively few “false positives” from contaminating populations. But the limited sensitivity and sparse overlap among the infrared and X-ray subsamples indicate that the sample is very incomplete with many “false negatives.” Maps, tables, and source descriptions are provided to guide further study of star formation in these regions. In particular, the nature of ultrahard X-ray protostellar candidates without known infrared counterparts needs to be elucidated.

Bayesian Analysis of the Cosmic Microwave Background

NASA Technical Reports Server (NTRS)

Jewell, Jeffrey

2007-01-01

There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background! Experiments designed to map the microwave sky are returning a flood of data (time streams of instrument response as a beam is swept over the sky) at several different frequencies (from 30 to 900 GHz), all with different resolutions and noise properties. The resulting analysis challenge is to estimate, and quantify our uncertainty in, the spatial power spectrum of the cosmic microwave background given the complexities of "missing data", foreground emission, and complicated instrumental noise. Bayesian formulation of this problem allows consistent treatment of many complexities including complicated instrumental noise and foregrounds, and can be numerically implemented with Gibbs sampling. Gibbs sampling has now been validated as an efficient, statistically exact, and practically useful method for low-resolution (as demonstrated on WMAP 1 and 3 year temperature and polarization data). Continuing development for Planck - the goal is to exploit the unique capabilities of Gibbs sampling to directly propagate uncertainties in both foreground and instrument models to total uncertainty in cosmological parameters.

Results from the Air Force Geophysics Laboratory survey catalog. [IR astronomy

NASA Technical Reports Server (NTRS)

Price, S. D.; Walker, R. G.

1977-01-01

Results of an IR survey program designed to obtain the spatial and brightness distributions of a representative sample of IR-emitting objects in the 3-30 micron range are analyzed. Small cryogenically cooled telescopes carried above the atmosphere on sounding rockets were employed in the research. Minimization of sky noise and photon background, experimental equipment, and data reduction techniques are discussed.

Spatial Displays and Spatial Instruments

NASA Technical Reports Server (NTRS)

Ellis, Stephen R. (Editor); Kaiser, Mary K. (Editor); Grunwald, Arthur J. (Editor)

1989-01-01

The conference proceedings topics are divided into two main areas: (1) issues of spatial and picture perception raised by graphical electronic displays of spatial information; and (2) design questions raised by the practical experience of designers actually defining new spatial instruments for use in new aircraft and spacecraft. Each topic is considered from both a theoretical and an applied direction. Emphasis is placed on discussion of phenomena and determination of design principles.

Nationwide Drinking Water Sampling Campaign for Exposure Assessments in Denmark

PubMed Central

Voutchkova, Denitza Dimitrova; Hansen, Birgitte; Ernstsen, Vibeke; Kristiansen, Søren Munch

2018-01-01

Nationwide sampling campaign of treated drinking water of groundwater origin was designed and implemented in Denmark in 2013. The main purpose of the sampling was to obtain data on the spatial variation of iodine concentration and speciation in treated drinking water, which was supplied to the majority of the Danish population. This data was to be used in future exposure and epidemiologic studies. The water supply sector (83 companies, owning 144 waterworks throughout Denmark) was involved actively in the planning and implementation process, which reduced significantly the cost and duration of data collection. The dataset resulting from this collaboration covers not only iodine species (I−, IO3−, TI), but also major elements and parameters (pH, electrical conductivity, DOC, TC, TN, F−, Cl−, NO3−, SO42−, Ca2+, Mg2+, K+, Na+) and a long list of trace elements (n = 66). The water samples represent 144 waterworks abstracting about 45% of the annual Danish groundwater abstraction for drinking water purposes, which supply about 2.5 million Danes (45% of all Danish residents). This technical note presents the design, implementation, and limitations of such a sampling design in detail in order (1) to facilitate the future use of this dataset, (2) to inform future replication studies, or (3) to provide an example for other researchers. PMID:29518987

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

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

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less

FIMic: design for ultimate 3D-integral microscopy of in-vivo biological samples

PubMed Central

Scrofani, G.; Sola-Pikabea, J.; Llavador, A.; Sanchez-Ortiga, E.; Barreiro, J. C.; Saavedra, G.; Garcia-Sucerquia, J.; Martínez-Corral, M.

2017-01-01

In this work, Fourier integral microscope (FIMic), an ultimate design of 3D-integral microscopy, is presented. By placing a multiplexing microlens array at the aperture stop of the microscope objective of the host microscope, FIMic shows extended depth of field and enhanced lateral resolution in comparison with regular integral microscopy. As FIMic directly produces a set of orthographic views of the 3D-micrometer-sized sample, it is suitable for real-time imaging. Following regular integral-imaging reconstruction algorithms, a 2.75-fold enhanced depth of field and 2-time better spatial resolution in comparison with conventional integral microscopy is reported. Our claims are supported by theoretical analysis and experimental images of a resolution test target, cotton fibers, and in-vivo 3D-imaging of biological specimens. PMID:29359107

Benthic macrofaunal structure and secondary production in tropical estuaries on the Eastern Marine Ecoregion of Brazil.

PubMed

Bissoli, Lorena B; Bernardino, Angelo F

2018-01-01

Tropical estuaries are highly productive and support diverse benthic assemblages within mangroves and tidal flats habitats. Determining differences and similarities of benthic assemblages within estuarine habitats and between regional ecosystems may provide scientific support for management of those ecosystems. Here we studied three tropical estuaries in the Eastern Marine Ecoregion of Brazil to assess the spatial variability of benthic assemblages from vegetated (mangroves) and unvegetated (tidal flats) habitats. A nested sampling design was used to determine spatial scales of variability in benthic macrofaunal density, biomass and secondary production. Habitat differences in benthic assemblage composition were evident, with mangrove forests being dominated by annelids (Oligochaeta and Capitellidae) whereas peracarid crustaceans were also abundant on tidal flats. Macrofaunal biomass, density and secondary production also differed between habitats and among estuaries. Those differences were related both to the composition of benthic assemblages and to random spatial variability, underscoring the importance of hierarchical sampling in estuarine ecological studies. Given variable levels of human impacts and predicted climate change effects on tropical estuarine assemblages in Eastern Brazil, our data support the use of benthic secondary production to address long-term changes and improved management of estuaries in Eastern Brazil.

On edge-aware path-based color spatial sampling for Retinex: from Termite Retinex to Light Energy-driven Termite Retinex

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Cordone, Roberto; Serapioni, Raul Paolo; Lecca, Michela

2017-05-01

Retinex theory estimates the human color sensation at any observed point by correcting its color based on the spatial arrangement of the colors in proximate regions. We revise two recent path-based, edge-aware Retinex implementations: Termite Retinex (TR) and Energy-driven Termite Retinex (ETR). As the original Retinex implementation, TR and ETR scan the neighborhood of any image pixel by paths and rescale their chromatic intensities by intensity levels computed by reworking the colors of the pixels on the paths. Our interest in TR and ETR is due to their unique, content-based scanning scheme, which uses the image edges to define the paths and exploits a swarm intelligence model for guiding the spatial exploration of the image. The exploration scheme of ETR has been showed to be particularly effective: its paths are local minima of an energy functional, designed to favor the sampling of image pixels highly relevant to color sensation. Nevertheless, since its computational complexity makes ETR poorly practicable, here we present a light version of it, named Light Energy-driven TR, and obtained from ETR by implementing a modified, optimized minimization procedure and by exploiting parallel computing.

Benthic macrofaunal structure and secondary production in tropical estuaries on the Eastern Marine Ecoregion of Brazil

PubMed Central

Bissoli, Lorena B.

2018-01-01

Tropical estuaries are highly productive and support diverse benthic assemblages within mangroves and tidal flats habitats. Determining differences and similarities of benthic assemblages within estuarine habitats and between regional ecosystems may provide scientific support for management of those ecosystems. Here we studied three tropical estuaries in the Eastern Marine Ecoregion of Brazil to assess the spatial variability of benthic assemblages from vegetated (mangroves) and unvegetated (tidal flats) habitats. A nested sampling design was used to determine spatial scales of variability in benthic macrofaunal density, biomass and secondary production. Habitat differences in benthic assemblage composition were evident, with mangrove forests being dominated by annelids (Oligochaeta and Capitellidae) whereas peracarid crustaceans were also abundant on tidal flats. Macrofaunal biomass, density and secondary production also differed between habitats and among estuaries. Those differences were related both to the composition of benthic assemblages and to random spatial variability, underscoring the importance of hierarchical sampling in estuarine ecological studies. Given variable levels of human impacts and predicted climate change effects on tropical estuarine assemblages in Eastern Brazil, our data support the use of benthic secondary production to address long-term changes and improved management of estuaries in Eastern Brazil. PMID:29507833

Design framework for a spectral mask for a plenoptic camera

NASA Astrophysics Data System (ADS)

Berkner, Kathrin; Shroff, Sapna A.

2012-01-01

Plenoptic cameras are designed to capture different combinations of light rays from a scene, sampling its lightfield. Such camera designs capturing directional ray information enable applications such as digital refocusing, rotation, or depth estimation. Only few address capturing spectral information of the scene. It has been demonstrated that by modifying a plenoptic camera with a filter array containing different spectral filters inserted in the pupil plane of the main lens, sampling of the spectral dimension of the plenoptic function is performed. As a result, the plenoptic camera is turned into a single-snapshot multispectral imaging system that trades-off spatial with spectral information captured with a single sensor. Little work has been performed so far on analyzing diffraction effects and aberrations of the optical system on the performance of the spectral imager. In this paper we demonstrate simulation of a spectrally-coded plenoptic camera optical system via wave propagation analysis, evaluate quality of the spectral measurements captured at the detector plane, and demonstrate opportunities for optimization of the spectral mask for a few sample applications.

Are there Benefits to Combining Regional Probabalistic Survey and Historic Targeted Environmental Monitoring Data to Improve Our Understanding of Overall Regional Estuary Environmental Status?

NASA Astrophysics Data System (ADS)

Dasher, D. H.; Lomax, T. J.; Bethe, A.; Jewett, S.; Hoberg, M.

2016-02-01

A regional probabilistic survey of 20 randomly selected stations, where water and sediments were sampled, was conducted over an area of Simpson Lagoon and Gwydyr Bay in the Beaufort Sea adjacent Prudhoe Bay, Alaska, in 2014. Sampling parameters included water column for temperature, salinity, dissolved oxygen, chlorophyll a, nutrients and sediments for macroinvertebrates, chemistry, i.e., trace metals and hydrocarbons, and grain size. The 2014 probabilistic survey design allows for inferences to be made of environmental status, for instance the spatial or aerial distribution of sediment trace metals within the design area sampled. Historically, since the 1970's a number of monitoring studies have been conducted in this estuary area using a targeted rather than regional probabilistic design. Targeted non-random designs were utilized to assess specific points of interest and cannot be used to make inferences to distributions of environmental parameters. Due to differences in the environmental monitoring objectives between probabilistic and targeted designs there has been limited assessment see if benefits exist to combining the two approaches. This study evaluates if a combined approach using the 2014 probabilistic survey sediment trace metal and macroinvertebrate results and historical targeted monitoring data can provide a new perspective on better understanding the environmental status of these estuaries.

Spatial and temporal variations in cadmium concentrations and burdens in the Pacific oyster (Crassostrea gigas) sampled from the Pacific north-west.

PubMed

Bendell, Leah I; Feng, Cindy

2009-08-01

Oysters from the north-west coast of Canada contain high levels of cadmium, a toxic metal, in amounts that exceed food safety guidelines for international markets. A first required step to determine the sources of cadmium is to identify possible spatial and temporal trends in the accumulation of cadmium by the oyster. To meet this objective, rather than sample wild and cultured oysters of unknown age and origin, an oyster "grow-out" experiment was initiated. Cultured oyster seed was suspended in the water column up to a depth of 7 m and the oyster seed allowed to mature a period of 3 years until market size. Oysters were sampled bimonthly and at time of sampling, temperature, chlorophyll-a, turbidity and salinity were measured. Oyster total shell length, dry tissue weights, cadmium concentrations (microg g(-1)) and burdens (microg of cadmium oyster(-1)) were determined. Oyster cadmium concentrations and burdens were then interpreted with respect to the spatial and temporal sampling design as well as to the measured physio-chemical and biotic variables. When expressed as a concentration, there was a marked seasonality with concentrations being greater in winter as compared in summer; however no spatial trend was evident. When expressed as a burden which corrects for differences in tissue mass, there was no seasonality, however cadmium oyster burdens increased from south to north. Comparison of cadmium accumulation rates oyster(-1) among sites indicated three locations, Webster Island, on the west side of Vancouver Island, and two within Desolation Sound, Teakerne Arm and Redonda Bay, where point sources of cadmium which are not present at all other sampling locations may be contributing to overall oyster cadmium burdens. Of the four physio-chemical factors measured only temperature and turbidity weakly correlated with tissue cadmium concentrations (r(2)=-0.13; p<0.05). By expressing oyster cadmium both as concentration and burden, regional and temporal patterns were demonstrated, which may have been missed if just concentration was determined.

Validation of Statistical Sampling Algorithms in Visual Sample Plan (VSP): Summary Report

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

Nuffer, Lisa L; Sego, Landon H.; Wilson, John E.

2009-02-18

The U.S. Department of Homeland Security, Office of Technology Development (OTD) contracted with a set of U.S. Department of Energy national laboratories, including the Pacific Northwest National Laboratory (PNNL), to write a Remediation Guidance for Major Airports After a Chemical Attack. The report identifies key activities and issues that should be considered by a typical major airport following an incident involving release of a toxic chemical agent. Four experimental tasks were identified that would require further research in order to supplement the Remediation Guidance. One of the tasks, Task 4, OTD Chemical Remediation Statistical Sampling Design Validation, dealt with statisticalmore » sampling algorithm validation. This report documents the results of the sampling design validation conducted for Task 4. In 2005, the Government Accountability Office (GAO) performed a review of the past U.S. responses to Anthrax terrorist cases. Part of the motivation for this PNNL report was a major GAO finding that there was a lack of validated sampling strategies in the U.S. response to Anthrax cases. The report (GAO 2005) recommended that probability-based methods be used for sampling design in order to address confidence in the results, particularly when all sample results showed no remaining contamination. The GAO also expressed a desire that the methods be validated, which is the main purpose of this PNNL report. The objective of this study was to validate probability-based statistical sampling designs and the algorithms pertinent to within-building sampling that allow the user to prescribe or evaluate confidence levels of conclusions based on data collected as guided by the statistical sampling designs. Specifically, the designs found in the Visual Sample Plan (VSP) software were evaluated. VSP was used to calculate the number of samples and the sample location for a variety of sampling plans applied to an actual release site. Most of the sampling designs validated are probability based, meaning samples are located randomly (or on a randomly placed grid) so no bias enters into the placement of samples, and the number of samples is calculated such that IF the amount and spatial extent of contamination exceeds levels of concern, at least one of the samples would be taken from a contaminated area, at least X% of the time. Hence, "validation" of the statistical sampling algorithms is defined herein to mean ensuring that the "X%" (confidence) is actually met.« less

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies

PubMed Central

Crandall, Eric D.; Liggins, Libby; Bongaerts, Pim; Treml, Eric A.

2016-01-01

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations. PMID:29491947

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies.

PubMed

Riginos, Cynthia; Crandall, Eric D; Liggins, Libby; Bongaerts, Pim; Treml, Eric A

2016-12-01

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations.

Learning to Think Spatially in an Undergraduate Interdisciplinary Computational Design Context: A Case Study

ERIC Educational Resources Information Center

Ben Youssef, Belgacem; Berry, Barbara

2012-01-01

Spatial thinking skills are vital for success in everyday living and work, not to mention the centrality of spatial reasoning in scientific discoveries, design-based disciplines, medicine, geosciences and mathematics to name a few. This case study describes a course in spatial thinking and communicating designed and delivered by an…

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

PubMed

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

2015-01-01

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

Hyper-spectral imaging in scanning-confocal-fluorescence microscopy using a novel broadband diffractive optic

NASA Astrophysics Data System (ADS)

Wang, Peng; Ebeling, Carl G.; Gerton, Jordan; Menon, Rajesh

In this paper, we demonstrate hyper-spectral imaging of fluorescent microspheres in a scanning-confocal-fluorescence microscope by spatially dispersing the spectra using a novel broadband diffractive optic, and applying a nonlinear optimization technique to extract the full-incident spectra. This broadband diffractive optic has a designed optical efficiency of over 90% across the entire visible spectrum. We used this technique to create two-color images of two fluorophores and also extracted their emission spectra with good fidelity. This method can be extended to image both spatially and spectrally overlapping fluorescent samples. Full control in the number of emission spectra and the feasibility of enhanced imaging speed are demonstrated as well.

Using a Multibeam Echosounder to Monitor AN Artificial Reef

NASA Astrophysics Data System (ADS)

Tassetti, A. N.; Malaspina, S.; Fabi, G.

2015-04-01

Artificial reefs (ARs) have become popular technological interventions in shallow water environments characterized by soft seabed for a wide number of purposes, from fisheries/environmental protection and enhancement to research and tourism. AR deployment has the potential for causing significant hydrographical and biological changes in the receiving environments and, in turn, ARs are strongly affected by the surrounding area in terms of spatial arrangement and structural integrity as well as colonization by benthic communities and finfish. In this context, ARs require a systematic monitoring program that a multibeam echosounder (MBES) can provide better than other sampling methods such as visual dives and ROV inspections that are not quantitative and often influenced by water visibility and diver experience/skills. In this paper, some subsequent MBES surveys of the Senigallia scientifically-planned AR (Northern Adriatic Sea) are presented and state-of-the art data processing and visualization techniques are used to draw post-reef deployment comparisons and quantify the evolution of the reef in terms of spatial arrangement and bulk volume. These multibeam surveys play a leading part in a general multi-year program, started simultaneously with the AR design and deployment and aimed to map how the reef structure quantitatively changes over time, as well as it affects the sea-bottom morphology and the fishery resource. All the data, surveyed over years making use of different sampling methods such as visual and instrumental echosounding observations and catch rate surveys, gain a mechanistic and predictive understanding of how the Senigallia AR functions ecologically and physically across spatial and temporal scales during its design life

Spatial Variability of Plant Available Water, Soil Organic Carbon, and Microbial Biomass under Divergent Land Uses: A Comparison among Regression-Kriging, Cokriging, and Regression-Cokriging

NASA Astrophysics Data System (ADS)

Kiani, M.; Hernandez Ramirez, G.; Quideau, S.

2016-12-01

Improved knowledge about the spatial variability of plant available water (PAW), soil organic carbon (SOC), and microbial biomass carbon (MBC) as affected by land-use systems can underpin the identification and inventory of beneficial ecosystem good and services in both agricultural and wild lands. Little research has been done that addresses the spatial patterns of PAW, SOC, and MBC under different land use types at a field scale. Therefore, we collected 56 soil samples (5-10 cm depth increment), using a nested cyclic sampling design within both a native grassland (NG) site and an irrigated cultivated (IC) site located near Brooks, Alberta. Using classical statistical and geostatistical methods, we characterized the spatial heterogeneities of PAW, SOC, and MBC under NG and IC using several geostatistical methods such as ordinary kriging (OK), regression-kriging (RK), cokriging (COK), and regression-cokriging (RCOK). Converting the native grassland to irrigated cultivated land altered soil pore distribution by reducing macroporosity which led to lower saturated water content and half hydraulic conductivity in IC compared to NG. This conversion also decreased the relative abundance of gram-negative bacteria, while increasing both the proportion of gram-positive bacteria and MBC concentration. At both studied sites, the best fitted spatial model was Gaussian based on lower RSS and higher R2 as criteria. The IC had stronger degree of spatial dependence and longer range of spatial auto-correlation revealing a homogenization of the spatial variability of soil properties as a result of intensive, recurrent agricultural activities. Comparison of OK, RK, COK, and RCOK approaches indicated that cokriging method had the best performance demonstrating a profound improvement in the accuracy of spatial estimations of PAW, SOC, and MBC. It seems that the combination of terrain covariates such as elevation and depth-to-water with kriging techniques offers more capability for incorporating explicit ancillary information in predictive soil mapping. Overall, identification of spatial patterns of soil properties in agricultural lands gives a bird's eye view to land owners to implement and improve management practices which lead to more sustainable production.

A Quantitative Approach for Collocating NEON's Sensor-Based Ecological Measurements and in-situ Field Sampling and Observations

NASA Astrophysics Data System (ADS)

Zulueta, R. C.; Metzger, S.; Ayres, E.; Luo, H.; Meier, C. L.; Barnett, D.; Sanclements, M.; Elmendorf, S.

2013-12-01

The National Ecological Observatory Network (NEON) is a continental-scale research platform currently in development to assess the causes of ecological change and biological responses to change across a projected 30-year timeframe. A suite of standardized sensor-based measurements (i.e., Terrestrial Instrument System (TIS) measurements) and in-situ field sampling and observations (i.e., Terrestrial Observation System (TOS) activities) will be conducted across 20 ecoclimatic domains in the U.S. where NEON is establishing 60 terrestrial research sites. NEON's TIS measurements and TOS activities are designed to observe the temporal and spatial dynamics of key drivers and ecological processes and responses to change within each of the 60 terrestrial research sites. The TIS measurements are non-destructive and designed to provide in-situ, continuous, and areally integrated observations of the surrounding ecosystem and environment, while TOS sampling and observation activities are designed to encompass a hierarchy of measurable biological states and processes including diversity, abundance, phenology, demography, infectious disease prevalence, ecohydrology, and biogeochemistry. To establish valid relationships between these drivers and site-specific responses, two contradicting requirements must be fulfilled: (i) both types of observations shall be representative of the same ecosystem, and (ii) they shall not significantly influence one another. Here we outline the theoretical background and algorithmic process for determining areas of mutual representativeness and exclusion around NEON's TIS measurements and develop a procedure which quantitatively optimizes this trade-off through: (i) quantifying the source area distributions of TIS measurements, (ii) determining the ratio of user-defined impact threshold to effective impact area for different TOS activities, and (iii) determining the range of feasible distances between TIS locations and TOS activities. This approach provides an evidence-based and repeatable method for combining sensor-based measurements and field sampling and observations at predefined levels of disturbance and spatial representativeness. The developed approach represents a general framework which is applicable to other environmental research sites where similar collocation is desired.

NEON: High Frequency Monitoring Network for Watershed-Scale Processes and Aquatic Ecology

NASA Astrophysics Data System (ADS)

Vance, J. M.; Fitzgerald, M.; Parker, S. M.; Roehm, C. L.; Goodman, K. J.; Bohall, C.; Utz, R.

2014-12-01

Networked high frequency hydrologic and water quality measurements needed to investigate physical and biogeochemical processes at the watershed scale and create robust models are limited and lacking standardization. Determining the drivers and mechanisms of ecological changes in aquatic systems in response to natural and anthropogenic pressures is challenging due to the large amounts of terrestrial, aquatic, atmospheric, biological, chemical, and physical data it requires at varied spatiotemporal scales. The National Ecological Observatory Network (NEON) is a continental-scale infrastructure project designed to provide data to address the impacts of climate change, land-use, and invasive species on ecosystem structure and function. Using a combination of standardized continuous in situ measurements and observational sampling, the NEON Aquatic array will produce over 200 data products across its spatially-distributed field sites for 30 years to facilitate spatiotemporal analysis of the drivers of ecosystem change. Three NEON sites in Alabama were chosen to address linkages between watershed-scale processes and ecosystem changes along an eco-hydrological gradient within the Tombigbee River Basin. The NEON Aquatic design, once deployed, will include continuous measurements of surface water physical, chemical, and biological parameters, groundwater level, temperature and conductivity and local meteorology. Observational sampling will include bathymetry, water chemistry and isotopes, and a suite of organismal sampling from microbes to macroinvertebrates to vertebrates. NEON deployed a buoy to measure the temperature profile of the Black Warrior River from July - November, 2013 to determine the spatiotemporal variability across the water column from a daily to seasonal scale. In July 2014 a series of water quality profiles were performed to assess the contribution of physical and biogeochemical drivers over a diurnal cycle. Additional river transects were performed across our site reach to capture the spatial variability of surface water parameters. Our preliminary data show differing response times to precipitation events and diurnal processes informing our infrastructure designs and sampling protocols aimed at providing data to address the eco-hydrological gradient.

The acute effects of cocoa flavanols on temporal and spatial attention.

PubMed

Karabay, Aytaç; Saija, Jefta D; Field, David T; Akyürek, Elkan G

2018-05-01

In this study, we investigated how the acute physiological effects of cocoa flavanols might result in specific cognitive changes, in particular in temporal and spatial attention. To this end, we pre-registered and implemented a randomized, double-blind, placebo- and baseline-controlled crossover design. A sample of 48 university students participated in the study and each of them completed the experimental tasks in four conditions (baseline, placebo, low dose, and high-dose flavanol), administered in separate sessions with a 1-week washout interval. A rapid serial visual presentation task was used to test flavanol effects on temporal attention and integration, and a visual search task was similarly employed to investigate spatial attention. Results indicated that cocoa flavanols improved visual search efficiency, reflected by reduced reaction time. However, cocoa flavanols did not facilitate temporal attention nor integration, suggesting that flavanols may affect some aspects of attention, but not others. Potential underlying mechanisms are discussed.

Utility of predicting group membership and the role of spatial visualization in becoming an engineer, physical scientist, or artist.

PubMed

Humphreys, L G; Lubinski, D; Yao, G

1993-04-01

This article has two themes: First, we explicate how the prediction of group membership can augment test validation designs restricted to prediction of individual differences in criterion performance. Second, we illustrate the utility of this methodology by documenting the importance of spatial visualization for becoming an engineer, physical scientist, or artist. This involved various longitudinal analyses on a sample of 400,000 high school students tracked after 11 years following their high school graduation. The predictive validities of Spatial-Math and Verbal-Math ability composites were established by successfully differentiating a variety of educational and occupational groups. One implication of our findings is that physical science and engineering disciplines appear to be losing many talented persons by restricting assessment to conventional mathematical and verbal abilities, such as those of the Scholastic Aptitude Test (SAT) and the Graduate Record Examination (GRE).

DENSITY: software for analysing capture-recapture data from passive detector arrays

USGS Publications Warehouse

Efford, M.G.; Dawson, D.K.; Robbins, C.S.

2004-01-01

A general computer-intensive method is described for fitting spatial detection functions to capture-recapture data from arrays of passive detectors such as live traps and mist nets. The method is used to estimate the population density of 10 species of breeding birds sampled by mist-netting in deciduous forest at Patuxent Research Refuge, Laurel, Maryland, U.S.A., from 1961 to 1972. Total density (9.9 ? 0.6 ha-1 mean ? SE) appeared to decline over time (slope -0.41 ? 0.15 ha-1y-1). The mean precision of annual estimates for all 10 species pooled was acceptable (CV(D) = 14%). Spatial analysis of closed-population capture-recapture data highlighted deficiencies in non-spatial methodologies. For example, effective trapping area cannot be assumed constant when detection probability is variable. Simulation may be used to evaluate alternative designs for mist net arrays where density estimation is a study goal.

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.

Short-term spatial and temporal variability in greenhouse gas fluxes in riparian zones.

PubMed

Vidon, P; Marchese, S; Welsh, M; McMillan, S

2015-08-01

Recent research indicates that riparian zones have the potential to contribute significant amounts of greenhouse gases (GHG: N2O, CO2, CH4) to the atmosphere. Yet, the short-term spatial and temporal variability in GHG emission in these systems is poorly understood. Using two transects of three static chambers at two North Carolina agricultural riparian zones (one restored, one unrestored), we show that estimates of the average GHG flux at the site scale can vary by one order of magnitude depending on whether the mean or the median is used as a measure of central tendency. Because the median tends to mute the effect of outlier points (hot spots and hot moments), we propose that both must be reported or that other more advanced spatial averaging techniques (e.g., kriging, area-weighted average) should be used to estimate GHG fluxes at the site scale. Results also indicate that short-term temporal variability in GHG fluxes (a few days) under seemingly constant temperature and hydrological conditions can be as large as spatial variability at the site scale, suggesting that the scientific community should rethink sampling protocols for GHG at the soil-atmosphere interface to include repeated measures over short periods of time at select chambers to estimate GHG emissions in the field. Although recent advances in technology provide tools to address these challenges, their cost is often too high for widespread implementation. Until technology improves, sampling design strategies will need to be carefully considered to balance cost, time, and spatial and temporal representativeness of measurements.

Kolmogorov-Smirnov test for spatially correlated data

USGS Publications Warehouse

Olea, R.A.; Pawlowsky-Glahn, V.

2009-01-01

The Kolmogorov-Smirnov test is a convenient method for investigating whether two underlying univariate probability distributions can be regarded as undistinguishable from each other or whether an underlying probability distribution differs from a hypothesized distribution. Application of the test requires that the sample be unbiased and the outcomes be independent and identically distributed, conditions that are violated in several degrees by spatially continuous attributes, such as topographical elevation. A generalized form of the bootstrap method is used here for the purpose of modeling the distribution of the statistic D of the Kolmogorov-Smirnov test. The innovation is in the resampling, which in the traditional formulation of bootstrap is done by drawing from the empirical sample with replacement presuming independence. The generalization consists of preparing resamplings with the same spatial correlation as the empirical sample. This is accomplished by reading the value of unconditional stochastic realizations at the sampling locations, realizations that are generated by simulated annealing. The new approach was tested by two empirical samples taken from an exhaustive sample closely following a lognormal distribution. One sample was a regular, unbiased sample while the other one was a clustered, preferential sample that had to be preprocessed. Our results show that the p-value for the spatially correlated case is always larger that the p-value of the statistic in the absence of spatial correlation, which is in agreement with the fact that the information content of an uncorrelated sample is larger than the one for a spatially correlated sample of the same size. ?? Springer-Verlag 2008.

Measurement of Spatial Ability: Construction and Validation of the Spatial Reasoning Instrument for Middle School Students

ERIC Educational Resources Information Center

Ramful, Ajay; Lowrie, Thomas; Logan, Tracy

2017-01-01

This article describes the development and validation of a newly designed instrument for measuring the spatial ability of middle school students (11-13 years old). The design of the Spatial Reasoning Instrument (SRI) is based on three constructs (mental rotation, spatial orientation, and spatial visualization) and is aligned to the type of spatial…

The improvement of precision for estimating the abundance of standing dead trees using auxiliary information under the FIA pot design

Treesearch

Hong Su An; David W. MacFarlane; Christopher W. Woodall

2012-01-01

Standing dead trees are an important component of forest ecosystems. However, reliable estimates of standing dead tree population parameters can be difficult to obtain due to their low abundance and spatial and temporal variation. After 1999, the Forest Inventory and Analysis (FIA) Program began collecting data for standing dead trees at the Phase 2 stage of sampling....

Effectiveness of timber harvesting BMPs: monitoring spatial and temporal dynamics of dissolved oxygen, nitrogen, and phosphorus in a low-gradient watershed, Louisiana

Treesearch

Abram DaSilva; Y. Jun Xu; George Ice; John Beebe; Richard Stich

2012-01-01

To test effectiveness of Louisiana’s voluntary best management practices (BMPs) at preventing water quality degradation from timber harvesting activities, a study with BACI design was conducted from 2006 through 2010 in the Flat Creek Watershed, north-central Louisiana. Water samples for nutrient analyses and measurements of stream flow and of in-stream dissolved...

The effect of short-range spatial variability on soil sampling uncertainty.

PubMed

Van der Perk, Marcel; de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Sansone, Umberto; Jeran, Zvonka; Jaćimović, Radojko

2008-11-01

This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.

An instrument design and sample strategy for measuring soil respiration in the coastal temperate rain forest

NASA Astrophysics Data System (ADS)

Nay, S. M.; D'Amore, D. V.

2009-12-01

The coastal temperate rainforest (CTR) along the northwest coast of North America is a large and complex mosaic of forests and wetlands located on an undulating terrain ranging from sea level to thousands of meters in elevation. This biome stores a dynamic portion of the total carbon stock of North America. The fate of the terrestrial carbon stock is of concern due to the potential for mobilization and export of this store to both the atmosphere as carbon respiration flux and ocean as dissolved organic and inorganic carbon flux. Soil respiration is the largest export vector in the system and must be accurately measured to gain any comprehensive understanding of how carbon moves though this system. Suitable monitoring tools capable of measuring carbon fluxes at small spatial scales are essential for our understanding of carbon dynamics at larger spatial scales within this complex assemblage of ecosystems. We have adapted instrumentation and developed a sampling strategy for optimizing replication of soil respiration measurements to quantify differences among spatially complex landscape units of the CTR. We start with the design of the instrument to ease the technological, ergonomic and financial barriers that technicians encounter in monitoring the efflux of CO2 from the soil. Our sampling strategy optimizes the physical efforts of the field work and manages for the high variation of flux measurements encountered in this difficult environment of rough terrain, dense vegetation and wet climate. Our soil respirometer incorporates an infra-red gas analyzer (LiCor Inc. LI-820) and an 8300 cm3 soil respiration chamber; the device is durable, lightweight, easy to operate and can be built for under $5000 per unit. The modest unit price allows for a multiple unit fleet to be deployed and operated in an intensive field monitoring campaign. We use a large 346 cm2 collar to accommodate as much micro spatial variation as feasible and to facilitate repeated measures for tracking temporal trends. Our collar design minimizes root interference yet provides a highly stable platform for coupling with the respirometer. Meso-scale variability characterized by large down woody debris, wind throw pits and mounds and surface roots is negotiated with by a hexagonal array of seven collars at two meter spacing (sample pod). Landscape scale variability is managed through stratification and replication amongst ecosystem types arrayed across a hydrologic gradient from bogs to forested wetlands to upland forests. Our strategy has allowed us to gather data sets consisting of approximately 1800 total observations with approximately 600 measurements per replication per year. Mean coefficients of variation (CV) at the collar (micro-scale) were approximately 0.67. The pod level mean CV was reduced to approximately 0.29 at the pod (meso-scale). The CV at the vegetation strata were 0.43, 0.18 and 0.21 for bog, forested wetland and upland forest respectively. With temperature and hydrological data we are able to measure and model carbon dynamics in this large and complex environment. The analysis of variability at the three spatial scales has confirmed that our approach is capturing and constraining the variability.

Unsupervised classification of multivariate geostatistical data: Two algorithms

NASA Astrophysics Data System (ADS)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

Variability of hazardous air pollutants in an urban area

NASA Astrophysics Data System (ADS)

Spicer, Chester W.; Buxton, Bruce E.; Holdren, Michael W.; Smith, Deborah L.; Kelly, Thomas J.; Rust, Steven W.; Pate, Alan D.; Sverdrup, George M.; Chuang, Jane C.

The variability of hazardous air pollutants (HAPs) is an important factor in determining human exposure to such chemicals, and in designing HAP measurement programs. This study has investigated the factors which contribute to HAP variability in an urban area. Six measurement sites separated by up to 12 km collected data with 3 h time resolution to examine spatial variability within neighborhoods and between neighborhoods. The measurements were made in Columbus, OH. The 3 h results also were used to study temporal variability, and duplicate samples collected at each site were used to determine the component of variability attributable to the measurement process. Hourly samples collected over 10 days at one site provided further insight into the temporal resolution needed to capture short-term peak concentrations. Measurements at the 6 spatial sites focused on 78 chemicals. Twenty-three of these species were found in at least 95% of the 3 h samples, and 39 chemicals were present at least 60% of the time. The relative standard deviations for most of these 39 frequently detected chemicals was 1.0 or lower. Variability was segmented into temporal, spatial, and measurement components. Temporal variation was the major contributor to HAP variability for 19 of the 39 frequently detected compounds, based on the 3 h data. Measurement imprecision contributed less than 25% for most of the volatile organic species, but 30% or more of the variability for carbonyl compounds, trace elements, and particle-bound extractable organic mass. Interestingly, the spatial component contributed less than 20% of the total variability for all the chemicals except sulfur. Based on the data with hourly resolution, peak to median ratios (hourly peak to 24 h median) averaged between 2 and 4 for most of the volatile organic compounds, but there were two species with peak to median ratios of about 10.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Prediction of Ba, Mn and Zn for tropical soils using iron oxides and magnetic susceptibility

NASA Astrophysics Data System (ADS)

Marques Júnior, José; Arantes Camargo, Livia; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angelica

2017-04-01

Agricultural activity is an important source of potentially toxic elements (PTEs) in soil worldwide but particularly in heavily farmed areas. Spatial distribution characterization of PTE contents in farming areas is crucial to assess further environmental impacts caused by soil contamination. Designing prediction models become quite useful to characterize the spatial variability of continuous variables, as it allows prediction of soil attributes that might be difficult to attain in a large number of samples through conventional methods. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Mn, Zn) and their spatial variability using iron oxides and magnetic susceptibility (MS). Soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, mineralogical properties, as well as magnetic susceptibility (MS). PTE prediction models were calibrated by multiple linear regression (MLR). MLR calibration accuracy was evaluated using the coefficient of determination (R2). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy by means of geostatistics. The high correlations between the attributes clay, MS, hematite (Hm), iron oxides extracted by sodium dithionite-citrate-bicarbonate (Fed), and iron oxides extracted using acid ammonium oxalate (Feo) with the elements Ba, Mn, and Zn enabled them to be selected as predictors for PTEs. Stepwise multiple linear regression showed that MS and Fed were the best PTE predictors individually, as they promoted no significant increase in R2 when two or more attributes were considered together. The MS-calibrated models for Ba, Mn, and Zn prediction exhibited R2 values of 0.88, 0.66, and 0.55, respectively. These are promising results since MS is a fast, cheap, and non-destructive tool, allowing the prediction of a large number of samples, which in turn enables detailed mapping of large areas. MS predicted values enabled the characterization and the understanding of spatial variability of the studied PTEs.

Identifying, characterizing and predicting spatial patterns of lacustrine groundwater discharge

NASA Astrophysics Data System (ADS)

Tecklenburg, Christina; Blume, Theresa

2017-10-01

Lacustrine groundwater discharge (LGD) can significantly affect lake water balances and lake water quality. However, quantifying LGD and its spatial patterns is challenging because of the large spatial extent of the aquifer-lake interface and pronounced spatial variability. This is the first experimental study to specifically study these larger-scale patterns with sufficient spatial resolution to systematically investigate how landscape and local characteristics affect the spatial variability in LGD. We measured vertical temperature profiles around a 0.49 km2 lake in northeastern Germany with a needle thermistor, which has the advantage of allowing for rapid (manual) measurements and thus, when used in a survey, high spatial coverage and resolution. Groundwater inflow rates were then estimated using the heat transport equation. These near-shore temperature profiles were complemented with sediment temperature measurements with a fibre-optic cable along six transects from shoreline to shoreline and radon measurements of lake water samples to qualitatively identify LGD patterns in the offshore part of the lake. As the hydrogeology of the catchment is sufficiently homogeneous (sandy sediments of a glacial outwash plain; no bedrock control) to avoid patterns being dominated by geological discontinuities, we were able to test the common assumptions that spatial patterns of LGD are mainly controlled by sediment characteristics and the groundwater flow field. We also tested the assumption that topographic gradients can be used as a proxy for gradients of the groundwater flow field. Thanks to the extensive data set, these tests could be carried out in a nested design, considering both small- and large-scale variability in LGD. We found that LGD was concentrated in the near-shore area, but alongshore variability was high, with specific regions of higher rates and higher spatial variability. Median inflow rates were 44 L m-2 d-1 with maximum rates in certain locations going up to 169 L m-2 d-1. Offshore LGD was negligible except for two local hotspots on steep steps in the lake bed topography. Large-scale groundwater inflow patterns were correlated with topography and the groundwater flow field, whereas small-scale patterns correlated with grain size distributions of the lake sediment. These findings confirm results and assumptions of theoretical and modelling studies more systematically than was previously possible with coarser sampling designs. However, we also found that a significant fraction of the variance in LGD could not be explained by these controls alone and that additional processes need to be considered. While regression models using these controls as explanatory variables had limited power to predict LGD rates, the results nevertheless encourage the use of topographic indices and sediment heterogeneity as an aid for targeted campaigns in future studies of groundwater discharge to lakes.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle.

PubMed

Ferrari, Renata; Marzinelli, Ezequiel M; Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F; Byrne, Maria; Malcolm, Hamish A; Williams, Stefan B; Steinberg, Peter D

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate 'no-take' and 'general-use' (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5-10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle

PubMed Central

Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F.; Byrne, Maria; Malcolm, Hamish A.; Williams, Stefan B.; Steinberg, Peter D.

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate ‘no-take’ and ‘general-use’ (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5–10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales. PMID:29547656

Deploying digital health data to optimize influenza surveillance at national and local scales

PubMed Central

Arab, Ali; Viboud, Cécile; Grenfell, Bryan T.; Bansal, Shweta

2018-01-01

The surveillance of influenza activity is critical to early detection of epidemics and pandemics and the design of disease control strategies. Case reporting through a voluntary network of sentinel physicians is a commonly used method of passive surveillance for monitoring rates of influenza-like illness (ILI) worldwide. Despite its ubiquity, little attention has been given to the processes underlying the observation, collection, and spatial aggregation of sentinel surveillance data, and its subsequent effects on epidemiological understanding. We harnessed the high specificity of diagnosis codes in medical claims from a database that represented 2.5 billion visits from upwards of 120,000 United States healthcare providers each year. Among influenza seasons from 2002-2009 and the 2009 pandemic, we simulated limitations of sentinel surveillance systems such as low coverage and coarse spatial resolution, and performed Bayesian inference to probe the robustness of ecological inference and spatial prediction of disease burden. Our models suggest that a number of socio-environmental factors, in addition to local population interactions, state-specific health policies, as well as sampling effort may be responsible for the spatial patterns in U.S. sentinel ILI surveillance. In addition, we find that biases related to spatial aggregation were accentuated among areas with more heterogeneous disease risk, and sentinel systems designed with fixed reporting locations across seasons provided robust inference and prediction. With the growing availability of health-associated big data worldwide, our results suggest mechanisms for optimizing digital data streams to complement traditional surveillance in developed settings and enhance surveillance opportunities in developing countries. PMID:29513661

Probing metamaterials with structured light

DOE PAGES

Xu, Yun; Sun, Jingbo; Walasik, Wiktor; ...

2016-11-03

Photonic metamaterials and metasurfaces are nanostructured optical materials engineered to enable properties that have not been found in nature. Optical characterization of these structures is a challenging task. We report a reliable technique that is particularly useful for characterization of phase properties introduced by small and spatially inhomogeneous samples of metamaterials and metasurfaces. The proposed structured light, or vortex based interferometric method is used to directly visualize phase changes introduced by subwavelength-thick nanostructures. In order to demonstrate the efficiency of the proposed technique, we designed and fabricated several metasurface samples consisting of metal nano-antennas introducing different phase shifts and experimentallymore » measured phase shifts of the transmitted light. The experimental results are in good agreement with numerical simulations and with the designed properties of the antenna arrays. Finally, due to the presence of the singularity in the vortex beam, one of the potential applications of the proposed approach based on structured light is step-by-step probing of small fractions of the micro-scale samples or images.« less

Visualization of electrochemically driven solid-state phase transformations using operando hard X-ray spectro-imaging

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

Li, Linsen; Chen-Wiegart, Yu-chen Karen; Wang, Jiajun

In situ techniques with high temporal, spatial and chemical resolution are key to understand ubiquitous solid-state phase transformations, which are crucial to many technological applications. Hard X-ray spectro-imaging can visualize electrochemically driven phase transformations but demands considerably large samples with strong absorption signal so far. Here we show a conceptually new data analysis method to enable operando visualization of mechanistically relevant weakly absorbing samples at the nanoscale and study electrochemical reaction dynamics of iron fluoride, a promising high-capacity conversion cathode material. In two specially designed samples with distinctive microstructure and porosity, we observe homogeneous phase transformations during both discharge andmore » charge, faster and more complete Li-storage occurring in porous polycrystalline iron fluoride, and further, incomplete charge reaction following a pathway different from conventional belief. In conclusion, these mechanistic insights provide guidelines for designing better conversion cathode materials to realize the promise of high-capacity lithium-ion batteries.« less

Visualization of electrochemically driven solid-state phase transformations using operando hard X-ray spectro-imaging

DOE PAGES

Li, Linsen; Chen-Wiegart, Yu-chen Karen; Wang, Jiajun; ...

2015-04-20

In situ techniques with high temporal, spatial and chemical resolution are key to understand ubiquitous solid-state phase transformations, which are crucial to many technological applications. Hard X-ray spectro-imaging can visualize electrochemically driven phase transformations but demands considerably large samples with strong absorption signal so far. Here we show a conceptually new data analysis method to enable operando visualization of mechanistically relevant weakly absorbing samples at the nanoscale and study electrochemical reaction dynamics of iron fluoride, a promising high-capacity conversion cathode material. In two specially designed samples with distinctive microstructure and porosity, we observe homogeneous phase transformations during both discharge andmore » charge, faster and more complete Li-storage occurring in porous polycrystalline iron fluoride, and further, incomplete charge reaction following a pathway different from conventional belief. In conclusion, these mechanistic insights provide guidelines for designing better conversion cathode materials to realize the promise of high-capacity lithium-ion batteries.« less

Sampling effects on the identification of roadkill hotspots: Implications for survey design.

PubMed

Santos, Sara M; Marques, J Tiago; Lourenço, André; Medinas, Denis; Barbosa, A Márcia; Beja, Pedro; Mira, António

2015-10-01

Although locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the accuracy of hotspot identification, using a dataset of vertebrate roadkills (n = 4427) recorded over a year of daily surveys along 37 km of roads. "True" hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of road-kills per segment. "Estimated" hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1-30 days). Overall, 24.3% of segments were "true" hotspots, concentrating 40.4% of roadkills. For different groups, "true" hotspots accounted from 6.8% (bats) to 29.7% (small birds) of road segments, concentrating from <40% (frogs and toads, snakes) to >60% (lizards, lagomorphs, carnivores) of roadkills. Spatial congruence between "true" and "estimated" hotspots declined rapidly with increasing time interval between surveys, due primarily to increasing false negatives (i.e., missing "true" hotspots). There were also false positives (i.e., wrong "estimated" hotspots), particularly at low sampling frequencies. Spatial accuracy decay with increasing time interval between surveys was higher for smaller-bodied (amphibians, reptiles, small birds, small mammals) than for larger-bodied species (birds of prey, hedgehogs, lagomorphs, carnivores). Results suggest that widely used surveys at weekly or longer intervals may produce poor estimates of roadkill hotspots, particularly for small-bodied species. Surveying daily or at two-day intervals may be required to achieve high accuracy in hotspot identification for multiple species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Passive sampling methods for contaminated sediments: Risk assessment and management

PubMed Central

Greenberg, Marc S; Chapman, Peter M; Allan, Ian J; Anderson, Kim A; Apitz, Sabine E; Beegan, Chris; Bridges, Todd S; Brown, Steve S; Cargill, John G; McCulloch, Megan C; Menzie, Charles A; Shine, James P; Parkerton, Thomas F

2014-01-01

This paper details how activity-based passive sampling methods (PSMs), which provide information on bioavailability in terms of freely dissolved contaminant concentrations (Cfree), can be used to better inform risk management decision making at multiple points in the process of assessing and managing contaminated sediment sites. PSMs can increase certainty in site investigation and management, because Cfree is a better predictor of bioavailability than total bulk sediment concentration (Ctotal) for 4 key endpoints included in conceptual site models (benthic organism toxicity, bioaccumulation, sediment flux, and water column exposures). The use of passive sampling devices (PSDs) presents challenges with respect to representative sampling for estimating average concentrations and other metrics relevant for exposure and risk assessment. These challenges can be addressed by designing studies that account for sources of variation associated with PSMs and considering appropriate spatial scales to meet study objectives. Possible applications of PSMs include: quantifying spatial and temporal trends in bioavailable contaminants, identifying and evaluating contaminant source contributions, calibrating site-specific models, and, improving weight-of-evidence based decision frameworks. PSM data can be used to assist in delineating sediment management zones based on likelihood of exposure effects, monitor remedy effectiveness, and, evaluate risk reduction after sediment treatment, disposal, or beneficial reuse after management actions. Examples are provided illustrating why PSMs and freely dissolved contaminant concentrations (Cfree) should be incorporated into contaminated sediment investigations and study designs to better focus on and understand contaminant bioavailability, more accurately estimate exposure to sediment-associated contaminants, and better inform risk management decisions. Research and communication needs for encouraging broader use are discussed. Integr Environ Assess Manag 2014;10:224–236. © 2014 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC. PMID:24343931

Estimation of the spatial autocorrelation function: consequences of sampling dynamic populations in space and time

Treesearch

Patrick C. Tobin

2004-01-01

The estimation of spatial autocorrelation in spatially- and temporally-referenced data is fundamental to understanding an organism's population biology. I used four sets of census field data, and developed an idealized space-time dynamic system, to study the behavior of spatial autocorrelation estimates when a practical method of sampling is employed. Estimates...

Recent changes in estuarine benthic and suprabenthic communities resulting from the development of harbour infrastructure.

PubMed

Dauvin, J C; Desroy, N; Janson, A L; Vallet, C; Duhamel, S

2006-01-01

Using a Before/During/After sampling protocol, the effects of the Le Havre harbour extension, which was started at the end of 2001, on the macrobenthic and suprabenthic communities in the eastern Bay of Seine (English Channel) were examined. As the construction phase has not yet been completed, the results presented here reflect only the data collected before and during the operations (September 2000 and 2002 for benthos sampling and March 2001, September 2001, October 2002 and March 2003 for suprabenthos sampling). Although bio-sedimentary changes did occur at the mouth of the Seine river, an analysis of benthic assemblages reveals that the dredging and construction operations do not seem to have influenced assemblage structure or the spatial distribution of organisms. Comparisons of the suprabenthic assemblages at each sampling date indicate that seasonal dynamics was mainly responsible for determining species distribution. We conclude that, 1 year into the harbour management plan, the observed changes in benthic and suprabenthic assemblage abundance do not exceed the range of spatial variability that exists naturally in the Seine estuary. Despite this compensatory actions designed to protect the aquatic habitats and to preserve a sustainable and healthy ecosystem have been added to the infrastructure development plan.

Spatial sampling considerations of the CERES (Clouds and Earth Radiant Energy System) instrument

NASA Astrophysics Data System (ADS)

Smith, G. L.; Manalo-Smith, Natividdad; Priestley, Kory

2014-10-01

The CERES (Clouds and Earth Radiant Energy System) instrument is a scanning radiometer with three channels for measuring Earth radiation budget. At present CERES models are operating aboard the Terra, Aqua and Suomi/NPP spacecraft and flights of CERES instruments are planned for the JPSS-1 spacecraft and its successors. CERES scans from one limb of the Earth to the other and back. The footprint size grows with distance from nadir simply due to geometry so that the size of the smallest features which can be resolved from the data increases and spatial sampling errors increase with nadir angle. This paper presents an analysis of the effect of nadir angle on spatial sampling errors of the CERES instrument. The analysis performed in the Fourier domain. Spatial sampling errors are created by smoothing of features which are the size of the footprint and smaller, or blurring, and inadequate sampling, that causes aliasing errors. These spatial sampling errors are computed in terms of the system transfer function, which is the Fourier transform of the point response function, the spacing of data points and the spatial spectrum of the radiance field.

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

USGS Publications Warehouse

Cross, Paul C.; Caillaud, Damien; Heisey, Dennis M.

2013-01-01

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.

PubMed

Roux, Emmanuel; Gaborit, Pascal; Romaña, Christine A; Girod, Romain; Dessay, Nadine; Dusfour, Isabelle

2013-12-01

Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value < 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region

PubMed Central

2013-01-01

Background Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum. Results We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value << 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001). Conclusions The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes. PMID:24289184

Integration and Evaluation of Microscope Adapter for the Ultra-Compact Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Smith-Dryden, S. D.; Blaney, D. L.; Van Gorp, B.; Mouroulis, P.; Green, R. O.; Sellar, R. G.; Rodriguez, J.; Wilson, D.

2012-12-01

Petrologic, diagenetic, impact and weathering processes often happen at scales that are not observable from orbit. On Earth, one of the most common things that a scientist does when trying to understand detailed geologic history is to create a thin section of the rock and study the mineralogy and texture. Unfortunately, sample preparation and manipulation with advanced instrumentation may be a resource intensive proposition (e.g. time, power, complexity) in-situ. Getting detailed mineralogy and textural information without sample preparation is highly desirable. Visible to short wavelength microimaging spectroscopy has the potential to provide this information without sample preparation. Wavelengths between 500-2600 nm are sensitive to a wide range of minerals including mafic, carbonates, clays, and sulfates. The Ultra-Compact Imaging Spectrometer (UCIS) has been developed as a low mass (<2.0 kg), low power (~5.2 W) Offner spectrometer, ideal for use on Mars rover or other in-situ platforms. The UCIS instrument with its HgCdTe detector provides a spectral resolution of 10 nm with a range of 500-2600 nm, in addition to a 30 degree field of view and a 1.35 mrad instantaneous field of view. (Van Gorp et al. 2011). To explore applications of this technology for microscale investigations, an f/10 microimaging adapter has been designed and integrated to allow imaging of samples. The spatial coverage of the instrument is 2.56 cm with sampling of 67.5 microns (380 spatial pixels). Because the adapter is slow relative to the UCIS detector, strong sample illumination is required. Light from the lamp box was directed through optical fiber bundles, and directed onto the sample at a high angle of incidence to provide dark field imaging. For data collection, a mineral sample is mounted on the microscope adapter and scanned by the detector as it is moved horizontally via actuator. Data from the instrument is stored as a xyz cube end product with one spectral and two spatial dimensions. Measured spectra are then divided out by a white referenced spectrum of a Spectralon® calibration standard to show reflectance. For mineral samples larger than the UCIS field of view, mosaicking may be used from multiple scans. Scans of various rocks and minerals taken with the microscope adapter will be shown and results will be presented. References: Van Gorp et al., Optical design and performance of the Ultra-Compact Imaging Spectrometer, SPIE Optics and Photonics, San Diego, Aug 21-25, 2011. Acknowledgements: This work has been conducted at the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration. Work was carried out with JPL Research and Technology Development Funding.

Microfluidic PDMS on paper (POP) devices.

PubMed

Shangguan, Jin-Wen; Liu, Yu; Pan, Jian-Bin; Xu, Bi-Yi; Xu, Jing-Juan; Chen, Hong-Yuan

2016-12-20

In this paper, we propose a generalized concept of microfluidic polydimethylsiloxane (PDMS) on paper (POP) devices, which combines well the merits of paper chips and PDMS chips. First, we optimized the conditions for accurate PDMS spatial patterning on paper, based on screen printing and a high temperature enabled superfast curing technique, which enables PDMS patterning to an accuracy of tens of microns in less than ten seconds. This, in turn, makes it available for seamless, reversible and reliable integration of the resulting paper layer with other PDMS channel structures. The integrated POP devices allow for both porous paper and smooth channels to be spatially defined on the devices, greatly extending the flexibility for designers to be able to construct powerful functional structures. To demonstrate the versatility of this design, a prototype POP device for the colorimetric analysis of liver function markers, serum protein, alkaline phosphatase (ALP) and aspartate aminotransferase (AST), was constructed. On this POP device, quantitative sample loading, mixing and multiplex analysis have all been realized.

YOUNG STELLAR POPULATIONS IN MYStIX STAR-FORMING REGIONS: CANDIDATE PROTOSTARS

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

Romine, Gregory; Feigelson, Eric D.; Getman, Konstantin V.

The Massive Young Star-Forming Complex in Infrared and X-ray (MYStIX) project provides a new census on stellar members of massive star-forming regions within 4 kpc. Here the MYStIX Infrared Excess catalog and Chandra -based X-ray photometric catalogs are mined to obtain high-quality samples of Class I protostars using criteria designed to reduce extragalactic and Galactic field star contamination. A total of 1109 MYStIX Candidate Protostars (MCPs) are found in 14 star-forming regions. Most are selected from protoplanetary disk infrared excess emission, but 20% are found from their ultrahard X-ray spectra from heavily absorbed magnetospheric flare emission. Two-thirds of the MCP sample ismore » newly reported here. The resulting samples are strongly spatially associated with molecular cores and filaments on Herschel far-infrared maps. This spatial agreement and other evidence indicate that the MCP sample has high reliability with relatively few “false positives” from contaminating populations. But the limited sensitivity and sparse overlap among the infrared and X-ray subsamples indicate that the sample is very incomplete with many “false negatives.” Maps, tables, and source descriptions are provided to guide further study of star formation in these regions. In particular, the nature of ultrahard X-ray protostellar candidates without known infrared counterparts needs to be elucidated.« less

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh

PubMed Central

Bi, Qifang; Azman, Andrew S.; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S.; Lessler, Justin

2016-01-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures. PMID:26866926

Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research

PubMed Central

Zhang, Shaocun; Cao, Xiaocang; Huang, He

2017-01-01

Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research. PMID:28286741

Systematic study of high-frequency ultrasonic transducer design for laser-scanning photoacoustic ophthalmoscopy

PubMed Central

Ma, Teng; Zhang, Xiangyang; Chiu, Chi Tat; Chen, Ruimin; Kirk Shung, K.; Zhou, Qifa; Jiao, Shuliang

2014-01-01

Abstract. Photoacoustic ophthalmoscopy (PAOM) is a high-resolution in vivo imaging modality that is capable of providing specific optical absorption information for the retina. A high-frequency ultrasonic transducer is one of the key components in PAOM, which is in contact with the eyelid through coupling gel during imaging. The ultrasonic transducer plays a crucial role in determining the image quality affected by parameters such as spatial resolution, signal-to-noise ratio, and field of view. In this paper, we present the results of a systematic study on a high-frequency ultrasonic transducer design for PAOM. The design includes piezoelectric material selection, frequency selection, and the fabrication process. Transducers of various designs were successfully applied for capturing images of biological samples in vivo. The performances of these designs are compared and evaluated. PMID:24441942

Systematic study of high-frequency ultrasonic transducer design for laser-scanning photoacoustic ophthalmoscopy.

PubMed

Ma, Teng; Zhang, Xiangyang; Chiu, Chi Tat; Chen, Ruimin; Kirk Shung, K; Zhou, Qifa; Jiao, Shuliang

2014-01-01

Photoacoustic ophthalmoscopy (PAOM) is a high-resolution in vivo imaging modality that is capable of providing specific optical absorption information for the retina. A high-frequency ultrasonic transducer is one of the key components in PAOM, which is in contact with the eyelid through coupling gel during imaging. The ultrasonic transducer plays a crucial role in determining the image quality affected by parameters such as spatial resolution, signal-to-noise ratio, and field of view. In this paper, we present the results of a systematic study on a high-frequency ultrasonic transducer design for PAOM. The design includes piezoelectric material selection, frequency selection, and the fabrication process. Transducers of various designs were successfully applied for capturing images of biological samples in vivo. The performances of these designs are compared and evaluated.

Development of a unique multi-contaminant air sampling device for a childhood asthma cohort in an agricultural environment.

PubMed

Armstrong, Jenna L; Fitzpatrick, Cole F; Loftus, Christine T; Yost, Michael G; Tchong-French, Maria; Karr, Catherine J

2013-09-01

This research describes the design, deployment, performance, and acceptability of a novel outdoor active air sampler to provide simultaneous measurements of multiple contaminants at timed intervals for the Aggravating Factors of Asthma in Rural Environment (AFARE) study-a longitudinal cohort of 50 children in Yakima Valley, Washington. The sampler was constructed of multiple sampling media connected to individual critical orifices and a rotary vane vacuum pump. It was connected to a timed control valve system to collect 24 hours samples every six days over 18 months. We describe a spatially representative approach with both quantitative and qualitative location criteria to deploy a network of 14 devices at participant residences in a rural region (20 × 60 km). Overall the sampler performed well, as the concurrent mean sample flow rates were within or above the ranges of recommended sampling rates for each exposure metric of interest. Acceptability was high among the study population of Hispanic farmworker participant households. The sampler design may prove useful for future urban and rural community-based studies with aims at collecting multiple contaminant data during specific time periods.

NEON's Mobile Deployment Platform: A Resource for Community Research

NASA Astrophysics Data System (ADS)

Sanclements, M.

2015-12-01

Here we provide an update on construction and validation of the NEON Mobile Deployment Platforms (MDPs) as well as a description of the infrastructure and sensors available to researchers in the future. The MDPs will provide the means to observe stochastic or spatially important events, gradients, or quantities that cannot be reliably observed using fixed location sampling (e.g. fires and floods). Due to the transient temporal and spatial nature of such events, the MDPs will be designed to accommodate rapid deployment for time periods up to ~ 1 year. Broadly, the MDPs will be comprised of infrastructure and instrumentation capable of functioning individually or in conjunction with one another to support observations of ecological change, as well as education, training and outreach.

The interpoint distance distribution as a descriptor of point patterns, with an application to spatial disease clustering.

PubMed

Bonetti, Marco; Pagano, Marcello

2005-03-15

The topic of this paper is the distribution of the distance between two points distributed independently in space. We illustrate the use of this interpoint distance distribution to describe the characteristics of a set of points within some fixed region. The properties of its sample version, and thus the inference about this function, are discussed both in the discrete and in the continuous setting. We illustrate its use in the detection of spatial clustering by application to a well-known leukaemia data set, and report on the results of a simulation experiment designed to study the power characteristics of the methods within that study region and in an artificial homogenous setting. Copyright (c) 2004 John Wiley & Sons, Ltd.

Sampling the sound field in auditoria using large natural-scale array measurements.

PubMed

Witew, Ingo B; Vorländer, Michael; Xiang, Ning

2017-03-01

Suitable data for spatial wave field analyses in concert halls need to satisfy the sampling theorem and hence requires densely spaced measurement positions over extended regions. The described measurement apparatus is capable of automatically sampling the sound field in auditoria over a surface of 5.30 m × 8.00 m to any appointed resolutions. In addition to discussing design features, a case study based on measured impulse responses is presented. The experimental data allow wave field animations demonstrating how sound propagating at grazing incidence over theater seating is scattered from rows of chairs (seat-dip effect). The visualized data of reflections and scattering from an auditorium's boundaries give insights and opportunities for advanced analyses.

Guidelines for Design and Sampling for Cyanobacterial Toxin and Taste-and-Odor Studies in Lakes and Reservoirs

USGS Publications Warehouse

Graham, Jennifer L.; Loftin, Keith A.; Ziegler, Andrew C.; Meyer, Michael T.

2008-01-01

Cyanobacteria and associated toxins and taste-and-odor compounds are of increasing environmental concern. However, consistent guidelines for the development of studies assessing cyanobacterial toxins and taste-and-odor compounds presently are not available. This report provides guidance for the development of scientific studies of cyanobacteria and associated by-products in lakes and reservoirs. Topics include: background information on cyanobacteria, toxins, and taste-and-odor compounds; spatial and temporal considerations that are unique to the cyanobacteria in lakes and reservoirs; common study types, objectives, and approaches for studies of cyanobacteria and associated toxins and taste-and-odor compounds; general guidelines for collecting samples; and information on sample handling, preparation, processing, and shipping.

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

Detailed characterisation of the incident neutron beam on the TOSCA spectrometer

NASA Astrophysics Data System (ADS)

Pinna, Roberto S.; Rudić, Svemir; Capstick, Matthew J.; McPhail, David J.; Pooley, Daniel E.; Howells, Gareth D.; Gorini, Giuseppe; Fernandez-Alonso, Felix

2017-10-01

We report a detailed characterisation of the incident neutron beam on the TOSCA spectrometer. A bespoke time-of-flight neutron monitor has been designed, constructed and used to perform extensive spatially resolved measurements of the absolute neutron flux and its underlying time structure at the instrument sample position. The obtained data give a quantitative understanding of the current instrument beyond neutronic simulations and provide a baseline in order to assess the performance of the upgraded instrument. At an average proton current-on-target of 153 μA (ISIS Target Station 1; at the time of measurements) we have found that the wavelength-integrated neutron flux (from 0.28 Å to 4.65 Å) at the position of the TOSCA instrument sample (spatially averaged across the 3 × 3cm2 surface centred around (0,0) position) is approximately 1 . 2 × 106 neutrons cm-2s-1, while the whole beam has a homogeneous distribution across the 3 . 0 × 3 . 5cm2 sample surface. The spectra reproduced the well-known shape of the neutrons moderated by the room temperature water moderator and exhibit a neutron flux of 7 . 3 × 105 neutrons cm-2s-1Å-1 at 1 Å.

Instantaneous field of view and spatial sampling of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

NASA Technical Reports Server (NTRS)

Chrien, Thomas G.; Green, Robert O.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures the upwelling radiance in 224 spectral bands. These data are required as images of approximately 11 by up to 100 km in extent at nominally 20 by 20 meter spatial resolution. In this paper we describe the underlying spatial sampling and spatial response characteristics of AVIRIS.

[Study of spatial stratified sampling strategy of Oncomelania hupensis snail survey based on plant abundance].

PubMed

Xun-Ping, W; An, Z

2017-07-27

Objective To optimize and simplify the survey method of Oncomelania hupensis snails in marshland endemic regions of schistosomiasis, so as to improve the precision, efficiency and economy of the snail survey. Methods A snail sampling strategy (Spatial Sampling Scenario of Oncomelania based on Plant Abundance, SOPA) which took the plant abundance as auxiliary variable was explored and an experimental study in a 50 m×50 m plot in a marshland in the Poyang Lake region was performed. Firstly, the push broom surveyed data was stratified into 5 layers by the plant abundance data; then, the required numbers of optimal sampling points of each layer through Hammond McCullagh equation were calculated; thirdly, every sample point in the line with the Multiple Directional Interpolation (MDI) placement scheme was pinpointed; and finally, the comparison study among the outcomes of the spatial random sampling strategy, the traditional systematic sampling method, the spatial stratified sampling method, Sandwich spatial sampling and inference and SOPA was performed. Results The method (SOPA) proposed in this study had the minimal absolute error of 0.213 8; and the traditional systematic sampling method had the largest estimate, and the absolute error was 0.924 4. Conclusion The snail sampling strategy (SOPA) proposed in this study obtains the higher estimation accuracy than the other four methods.

Photography activities for developing students’ spatial orientation and spatial visualization

NASA Astrophysics Data System (ADS)

Hendroanto, Aan; van Galen, Frans; van Eerde, D.; Prahmana, R. C. I.; Setyawan, F.; Istiandaru, A.

2017-12-01

Spatial orientation and spatial visualization are the foundation of students’ spatial ability. They assist students’ performance in learning mathematics, especially geometry. Considering its importance, the present study aims to design activities to help young learners developing their spatial orientation and spatial visualization ability. Photography activity was chosen as the context of the activity to guide and support the students. This is a design research study consisting of three phases: 1) preparation and designing 2) teaching experiment, and 3) retrospective analysis. The data is collected by tests and interview and qualitatively analyzed. We developed two photography activities to be tested. In the teaching experiments, 30 students of SD Laboratorium UNESA, Surabaya were involved. The results showed that the activities supported the development of students’ spatial orientation and spatial visualization indicated by students’ learning progresses, answers, and strategies when they solved the problems in the activities.

Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

PubMed

Hatipoglu, Nuh; Bilgin, Gokhan

2017-10-01

In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.

The design of sampling transects for characterizing water quality in estuaries

USGS Publications Warehouse

Jassby, A.D.; Cole, B.E.; Cloern, J.E.

1997-01-01

The high spatial variability of estuaries poses a challenge for characterizing estuarine water quality. This problem was examined by conducting monthly high-resolution transects for several water quality variables (chlorophyll a, suspended particulate matter and salinity) in San Francisco Bay (California, U.S.A.). Using these data, six different ways of choosing station locations along a transect, in order to estimate mean conditions, were compared. In addition, 11 approaches to estimating the variance of the transect mean when stations are equally spaced were compared, and the relationship between variance of the estimated transect mean and number of stations was determined. The results provide guidelines for sampling along the axis of an estuary: (1) Choose as many equally-spaced stations as practical; (2) estimate the variance of the mean y?? by var (y??)=(1/10n2)??(j=2)/(n) (y(j)-y(j-1)2, where y1,...,y(n) are the measurements at the n stations; and (3) attain the desired precision by adjusting the number of stations according to var(y??)???1/n2. The inverse power of 2 in the last step is a consequence of the underlying spatial correlation structure in San Francisco Bay; more studies of spatial structure at other estuaries are needed to determine the generality of this relationship.

Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

DOE PAGES

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.; ...

2017-01-24

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

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

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

The Effects of Computer-Aided Design Software on Engineering Students' Spatial Visualisation Skills

ERIC Educational Resources Information Center

Kösa, Temel; Karakus, Fatih

2018-01-01

The purpose of this study was to determine the influence of computer-aided design (CAD) software-based instruction on the spatial visualisation skills of freshman engineering students in a computer-aided engineering drawing course. A quasi-experimental design was applied, using the Purdue Spatial Visualization Test-Visualization of Rotations…

Random field theory to interpret the spatial variability of lacustrine soils

NASA Astrophysics Data System (ADS)

Russo, Savino; Vessia, Giovanna

2015-04-01

The lacustrine soils are quaternary soils, dated from Pleistocene to Holocene periods, generated in low-energy depositional environments and characterized by soil mixture of clays, sands and silts with alternations of finer and coarser grain size layers. They are often met at shallow depth filling several tens of meters of tectonic or erosive basins typically placed in internal Appenine areas. The lacustrine deposits are often locally interbedded by detritic soils resulting from the failure of surrounding reliefs. Their heterogeneous lithology is associated with high spatial variability of physical and mechanical properties both along horizontal and vertical directions. The deterministic approach is still commonly adopted to accomplish the mechanical characterization of these heterogeneous soils where undisturbed sampling is practically not feasible (if the incoherent fraction is prevalent) or not spatially representative (if the cohesive fraction prevails). The deterministic approach consists on performing in situ tests, like Standard Penetration Tests (SPT) or Cone Penetration Tests (CPT) and deriving design parameters through "expert judgment" interpretation of the measure profiles. These readings of tip and lateral resistances (Rp and RL respectively) are almost continuous but highly variable in soil classification according to Schmertmann (1978). Thus, neglecting the spatial variability cannot be the best strategy to estimated spatial representative values of physical and mechanical parameters of lacustrine soils to be used for engineering applications. Hereafter, a method to draw the spatial variability structure of the aforementioned measure profiles is presented. It is based on the theory of the Random Fields (Vanmarcke 1984) applied to vertical readings of Rp measures from mechanical CPTs. The proposed method relies on the application of the regression analysis, by which the spatial mean trend and fluctuations about this trend are derived. Moreover, the scale of fluctuation is calculated to measure the maximum length beyond which profiles of measures are independent. The spatial mean trend can be used to identify "quasi-homogeneous" soil layers where the standard deviation and the scale of fluctuation can be calculated. In this study, five Rp profiles performed in the lacustrine deposits of the high River Pescara Valley have been analyzed. There, silty clay deposits with thickness ranging from a few meters to about 60m, and locally rich in sands and peats, are investigated. In this study, vertical trends of Rp profiles have been derived to be converted into design parameter mean trends. Furthermore, the variability structure derived from Rp readings can be propagated to design parameters to calculate the "characteristic values" requested by the European building codes. References Schmertmann J.H. 1978. Guidelines for Cone Penetration Test, Performance and Design. Report No. FHWA-TS-78-209, U.S. Department of Transportation, Washington, D.C., pp. 145. Vanmarcke E.H. 1984. Random Fields, analysis and synthesis. Cambridge (USA): MIT Press.

Micron Scale Mapping and Depth Profiling of Organic Compounds in Geologic Material: Femtosecond - Laser Desorption Laser Postionization - Mass Spectrometry (fs-LDPI-MS)

NASA Astrophysics Data System (ADS)

Pasterski, M. J.; Barry, G. E.; Hanley, L.; Kenig, F. P. H.

2017-12-01

One of the major challenges within the field of organic geochemistry is to determine whether an observed biomarker signature is indigenous (emplaced during sedimentation), non-indigenous (emplaced after sedimentation) or contaminant (incorporated during sampling, storage or analysis). The challenge of determining the mode of emplacement of an observed biomarker signature is accentuated in analyses of Precambrian samples, and may be an issue upon Mars sample return. Current geochemical techniques (e.g. gas chromatography-mass spectrometry, GC-MS, GC×GC-MS) can determine the composition and structure of the organic constituents of a sample. However, the preparatory steps necessary prior to GC-MS analysis (sample crushing, solvent extraction) make it impossible to determine the precise spatial distribution of organic molecules within rocks and sediments. Here, we will present data from the first set of micron (2-5 μm width × 8 μm depth) resolution MS-images of organic compounds in geologic material. Fs-LDPI-MS was utilized to create MS-images of organic compounds in four samples: (1) an Antarctic igneous dike used as a sample blank; (2) a 93 million year-old (Ma) burrowed carbonate collected near Pueblo, CO; (3) a 164 Ma organic rich mudstone collected in central England; and (4) a 2680 Ma metasediment collected in Timmins, ON, Canada. Prior to this study, all samples had been analyzed via GC-MS to determine the bulk hydrocarbon composition. For this study, thick sections (70-100 μm thick) were prepared in-house using custom-designed clean preparation techniques. Petrographic maps of the thick sections were created to highlight geologic features such as burrows (sample 2), particulate organic matter (sample 3) and hydrothermal veins (sample 4). Fs-LDPI-MS analysis was performed on the mapped thick sections. MS-images of targeted organic compounds were created, and the MS-images were overlain with the petrographic maps to determine the spatial distribution of the organic compounds relative to host rock features. We were able to use the spatial distribution of the targeted organic compounds to unambiguously characterize them as either indigenous, non-indigenous or contaminants. This technique is applicable to the analysis of both Precambrian samples and extraterrestrial material.

Lognormal kriging for the assessment of reliability in groundwater quality control observation networks

USGS Publications Warehouse

Candela, L.; Olea, R.A.; Custodio, E.

1988-01-01

Groundwater quality observation networks are examples of discontinuous sampling on variables presenting spatial continuity and highly skewed frequency distributions. Anywhere in the aquifer, lognormal kriging provides estimates of the variable being sampled and a standard error of the estimate. The average and the maximum standard error within the network can be used to dynamically improve the network sampling efficiency or find a design able to assure a given reliability level. The approach does not require the formulation of any physical model for the aquifer or any actual sampling of hypothetical configurations. A case study is presented using the network monitoring salty water intrusion into the Llobregat delta confined aquifer, Barcelona, Spain. The variable chloride concentration used to trace the intrusion exhibits sudden changes within short distances which make the standard error fairly invariable to changes in sampling pattern and to substantial fluctuations in the number of wells. ?? 1988.

A stratified two-stage sampling design for digital soil mapping in a Mediterranean basin

NASA Astrophysics Data System (ADS)

Blaschek, Michael; Duttmann, Rainer

2015-04-01

The quality of environmental modelling results often depends on reliable soil information. In order to obtain soil data in an efficient manner, several sampling strategies are at hand depending on the level of prior knowledge and the overall objective of the planned survey. This study focuses on the collection of soil samples considering available continuous secondary information in an undulating, 16 km²-sized river catchment near Ussana in southern Sardinia (Italy). A design-based, stratified, two-stage sampling design has been applied aiming at the spatial prediction of soil property values at individual locations. The stratification based on quantiles from density functions of two land-surface parameters - topographic wetness index and potential incoming solar radiation - derived from a digital elevation model. Combined with four main geological units, the applied procedure led to 30 different classes in the given test site. Up to six polygons of each available class were selected randomly excluding those areas smaller than 1ha to avoid incorrect location of the points in the field. Further exclusion rules were applied before polygon selection masking out roads and buildings using a 20m buffer. The selection procedure was repeated ten times and the set of polygons with the best geographical spread were chosen. Finally, exact point locations were selected randomly from inside the chosen polygon features. A second selection based on the same stratification and following the same methodology (selecting one polygon instead of six) was made in order to create an appropriate validation set. Supplementary samples were obtained during a second survey focusing on polygons that have either not been considered during the first phase at all or were not adequately represented with respect to feature size. In total, both field campaigns produced an interpolation set of 156 samples and a validation set of 41 points. The selection of sample point locations has been done using ESRI software (ArcGIS) extended by Hawth's Tools and later on its replacement the Geospatial Modelling Environment (GME). 88% of all desired points could actually be reached in the field and have been successfully sampled. Our results indicate that the sampled calibration and validation sets are representative for each other and could be successfully used as interpolation data for spatial prediction purposes. With respect to soil textural fractions, for instance, equal multivariate means and variance homogeneity were found for the two datasets as evidenced by significant (P > 0.05) Hotelling T²-test (2.3 with df1 = 3, df2 = 193) and Bartlett's test statistics (6.4 with df = 6). The multivariate prediction of clay, silt and sand content using a neural network residual cokriging approach reached an explained variance level of 56%, 47% and 63%. Thus, the presented case study is a successful example of considering readily available continuous information on soil forming factors such as geology and relief as stratifying variables for designing sampling schemes in digital soil mapping projects.

Magnetic field pattern synthesis and its application in targeted drug delivery: Design and implementation.

PubMed

Hajiaghajani, Amirhossein; Abdolali, Ali

2018-05-01

In cancer therapy, magnetic drug targeting is considered as an effective treatment to reduce chemotherapy's side effects. The accurate design and shaping of magnetic fields are crucial for healthy cells to be immune from chemotherapeutics. In this paper, arbitrary 2-dimensional spatial patterns of magnetic fields from DC to megahertz are represented in terms of spatial Fourier spectra with sinusoidal eigenfunctions. Realization of each spatial frequency was investigated by a set of elliptical coils. Therefore, it is shown that the desired pattern was synthesized by simultaneous use of coil sets. Currents running on each set were obtained via fast and straightforward analytical Fourier series calculation. Experimentally scanned sample patterns were in close agreement with full wave analysis. Discussions include the evaluation of the Fourier series approximation error and cross-polarization of produced magnetic fields. It was observed that by employing the controlled magnetic field produced by the proposed setup, we were able to steer therapeutic particles toward the right or left half-spheres of the breast, with an efficiency of 90%. Such a pattern synthesizer may be employed in numerous human arteries as well as other bioelectromagnetic patterning applications, e.g., wireless power transfer, magnetic innervation, and tomography. Bioelectromagnetics. 39:325-338, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Occupancy Modeling Species-Environment Relationships with Non-ignorable Survey Designs.

PubMed

Irvine, Kathryn M; Rodhouse, Thomas J; Wright, Wilson J; Olsen, Anthony R

2018-05-26

Statistical models supporting inferences about species occurrence patterns in relation to environmental gradients are fundamental to ecology and conservation biology. A common implicit assumption is that the sampling design is ignorable and does not need to be formally accounted for in analyses. The analyst assumes data are representative of the desired population and statistical modeling proceeds. However, if datasets from probability and non-probability surveys are combined or unequal selection probabilities are used, the design may be non ignorable. We outline the use of pseudo-maximum likelihood estimation for site-occupancy models to account for such non-ignorable survey designs. This estimation method accounts for the survey design by properly weighting the pseudo-likelihood equation. In our empirical example, legacy and newer randomly selected locations were surveyed for bats to bridge a historic statewide effort with an ongoing nationwide program. We provide a worked example using bat acoustic detection/non-detection data and show how analysts can diagnose whether their design is ignorable. Using simulations we assessed whether our approach is viable for modeling datasets composed of sites contributed outside of a probability design Pseudo-maximum likelihood estimates differed from the usual maximum likelihood occu31 pancy estimates for some bat species. Using simulations we show the maximum likelihood estimator of species-environment relationships with non-ignorable sampling designs was biased, whereas the pseudo-likelihood estimator was design-unbiased. However, in our simulation study the designs composed of a large proportion of legacy or non-probability sites resulted in estimation issues for standard errors. These issues were likely a result of highly variable weights confounded by small sample sizes (5% or 10% sampling intensity and 4 revisits). Aggregating datasets from multiple sources logically supports larger sample sizes and potentially increases spatial extents for statistical inferences. Our results suggest that ignoring the mechanism for how locations were selected for data collection (e.g., the sampling design) could result in erroneous model-based conclusions. Therefore, in order to ensure robust and defensible recommendations for evidence-based conservation decision-making, the survey design information in addition to the data themselves must be available for analysts. Details for constructing the weights used in estimation and code for implementation are provided. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Using larval fish community structure to guide long-term monitoring of fish spawning activity

USGS Publications Warehouse

Pritt, Jeremy J.; Roseman, Edward F.; Ross, Jason E.; DeBruyne, Robin L.

2015-01-01

Larval fishes provide a direct indication of spawning activity and may therefore be useful for long-term monitoring efforts in relation to spawning habitat restoration. However, larval fish sampling can be time intensive and costly. We sought to understand the spatial and temporal structure of larval fish communities in the St. Clair–Detroit River system, Michigan–Ontario, to determine whether targeted larval fish sampling can be made more efficient for long-term monitoring. We found that larval fish communities were highly nested, with lower river segments and late-spring samples containing the highest genus richness of larval fish. We created four sampling scenarios for each river system: (1) using all available data, (2) limiting temporal sampling to late spring, (3) limiting spatial sampling to lower river segments only, and (4) limiting both spatial and temporal sampling. By limiting the spatial extent of sampling to lower river sites and/or limiting the temporal extent to the late-spring period, we found that effort could be reduced by more than 50% while maintaining over 75% of the observed and estimated total genus richness. Similarly, limiting the sampling effort to lower river sites and/or the late-spring period maintained between 65% and 93% of the observed richness of lithophilic-spawning genera and invasive genera. In general, community composition remained consistent among sampling scenarios. Targeted sampling offers a lower-cost alternative to exhaustive spatial and temporal sampling and may be more readily incorporated into long-term monitoring.

Effects of spatial scale of sampling on food web structure

PubMed Central

Wood, Spencer A; Russell, Roly; Hanson, Dieta; Williams, Richard J; Dunne, Jennifer A

2015-01-01

This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two-thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power-law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling. PMID:26380704

Persistent spatial information in the frontal eye field during object-based short-term memory.

PubMed

Clark, Kelsey L; Noudoost, Behrad; Moore, Tirin

2012-08-08

Spatial attention is known to gate entry into visual short-term memory, and some evidence suggests that spatial signals may also play a role in binding features or protecting object representations during memory maintenance. To examine the persistence of spatial signals during object short-term memory, the activity of neurons in the frontal eye field (FEF) of macaque monkeys was recorded during an object-based delayed match-to-sample task. In this task, monkeys were trained to remember an object image over a brief delay, regardless of the locations of the sample or target presentation. FEF neurons exhibited visual, delay, and target period activity, including selectivity for sample location and target location. Delay period activity represented the sample location throughout the delay, despite the irrelevance of spatial information for successful task completion. Furthermore, neurons continued to encode sample position in a variant of the task in which the matching stimulus never appeared in their response field, confirming that FEF maintains sample location independent of subsequent behavioral relevance. FEF neurons also exhibited target-position-dependent anticipatory activity immediately before target onset, suggesting that monkeys predicted target position within blocks. These results show that FEF neurons maintain spatial information during short-term memory, even when that information is irrelevant for task performance.

TRMM .25 deg x .25 deg Gridded Precipitation Text Product

NASA Technical Reports Server (NTRS)

Stocker, Erich; Kelley, Owen

2009-01-01

Since the launch of the Tropical Rainfall Measuring Mission (TRMM), the Precipitation Measurement Missions science team has endeavored to provide TRMM precipitation retrievals in a variety of formats that are more easily usable by the broad science community than the standard Hierarchical Data Format (HDF) in which TRMM data is produced and archived. At the request of users, the Precipitation Processing System (PPS) has developed a .25 x .25 gridded product in an easily used ASCII text format. The entire TRMM mission data has been made available in this format. The paper provides the details of this new precipitation product that is designated with the TRMM designator 3G68.25. The format is packaged into daily files. It provides hourly precipitation information from the TRMM microwave imager (TMI), precipitation radar (PR), and TMI/PR combined rain retrievals. A major advantage of this approach is the inclusion only of rain data, compression when a particular grid has no rain from the PR or combined, and its direct ASCII text format. For those interested only in rain retrievals and whether rain is convection or stratiform, these products provide a huge reduction in the data volume inherent in the standard TRMM products. This paper provides examples of the 3G68 data products and their uses. It also provides information about C tools that can be used to aggregate daily files into larger time samples. In addition, it describes the possibilities inherent in the spatial sampling which allows resampling into coarser spatial sampling. The paper concludes with information about downloading the gridded text data products.

Design & implementation of distributed spatial computing node based on WPS

NASA Astrophysics Data System (ADS)

Liu, Liping; Li, Guoqing; Xie, Jibo

2014-03-01

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed.

UTOOLS: microcomputer software for spatial analysis and landscape visualization.

Treesearch

Alan A. Ager; Robert J. McGaughey

1997-01-01

UTOOLS is a collection of programs designed to integrate various spatial data in a way that allows versatile spatial analysis and visualization. The programs were designed for watershed-scale assessments in which a wide array of resource data must be integrated, analyzed, and interpreted. UTOOLS software combines raster, attribute, and vector data into "spatial...

Survey design for lakes and reservoirs in the United States to assess contaminants in fish tissue.

PubMed

Olsen, Anthony R; Snyder, Blaine D; Stahl, Leanne L; Pitt, Jennifer L

2009-03-01

The National Lake Fish Tissue Study (NLFTS) was the first survey of fish contamination in lakes and reservoirs in the 48 conterminous states based on a probability survey design. This study included the largest set (268) of persistent, bioaccumulative, and toxic (PBT) chemicals ever studied in predator and bottom-dwelling fish species. The U.S. Environmental Protection Agency (USEPA) implemented the study in cooperation with states, tribal nations, and other federal agencies, with field collection occurring at 500 lakes and reservoirs over a four-year period (2000-2003). The sampled lakes and reservoirs were selected using a spatially balanced unequal probability survey design from 270,761 lake objects in USEPA's River Reach File Version 3 (RF3). The survey design selected 900 lake objects, with a reserve sample of 900, equally distributed across six lake area categories. A total of 1,001 lake objects were evaluated to identify 500 lake objects that met the study's definition of a lake and could be accessed for sampling. Based on the 1,001 evaluated lakes, it was estimated that a target population of 147,343 (+/-7% with 95% confidence) lakes and reservoirs met the NLFTS definition of a lake. Of the estimated 147,343 target lakes, 47% were estimated not to be sampleable either due to landowner access denial (35%) or due to physical barriers (12%). It was estimated that a sampled population of 78,664 (+/-12% with 95% confidence) lakes met the NLFTS lake definition, had either predator or bottom-dwelling fish present, and could be sampled.

Spatial Mapping of Organic Carbon in Returned Samples from Mars

NASA Astrophysics Data System (ADS)

Siljeström, S.; Fornaro, T.; Greenwalt, D.; Steele, A.

2018-04-01

To map organic material spatially to minerals present in the sample will be essential for the understanding of the origin of any organics in returned samples from Mars. It will be shown how ToF-SIMS may be used to map organics in samples from Mars.

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey.

PubMed

Bayramin, Ilhami; Basaran, Mustafa; Erpul, Günay; Canga, Mustafa R

2008-05-01

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri-Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0-10 cm (D1) and 10-20 cm (D2) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect-sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.

Multiple spatial scale analyses provide new clues on patterns and drivers of deep-sea nematode diversity

NASA Astrophysics Data System (ADS)

Danovaro, Roberto; Carugati, Laura; Corinaldesi, Cinzia; Gambi, Cristina; Guilini, Katja; Pusceddu, Antonio; Vanreusel, Ann

2013-08-01

The deep sea is the largest biome of the biosphere. The knowledge of the spatial variability of deep-sea biodiversity is one of the main challenges of marine ecology and evolutionary biology. The choice of the observational spatial scale is assumed to play a key role for understanding processes structuring the deep-sea benthic communities and one of the most typical features of marine biodiversity distribution is the existence of bathymetric gradients. However, the analysis of biodiversity bathymetric gradients and the associated changes in species composition (beta diversity) typically compared large depth ranges (with intervals of 500 to 1000 or even 2000 m depth among sites). To test whether significant changes in alpha and beta diversity occur also at fine-scale bathymetric gradients (i.e., within few hundred-meter depth intervals) the variability of deep-sea nematode biodiversity and assemblage composition along a bathymetric transect (200-1200 m depth) with intervals of 200 m among sampling depths, was investigated. A hierarchical sampling strategy for the analysis of nematode species richness, beta diversity, functional (trophic) diversity, and related environmental variables, was used. The results indicate the lack of significant differences in taxonomic and functional diversity across sampling depths, but the presence of high beta diversity at all spatial scales investigated: between cores collected from the same box corer (on average 56%), among deployments at the same depth (58%), and between all sampling depths (62%). Such high beta diversity is influenced by the presence of small-scale patchiness in the deep sea and is also related to the large number of rare or very rare species (typically accounting for >80% of total species richness). Moreover, the number of ubiquitous nematode species across all sampling depths is quite low (ca. 15%). Multiple regression analyses provide evidence that such patterns could be related to the different availability, composition and size spectra of food particles in the sediments. Additionally, though to a lesser extent, our results indicate, that selective predation can influence the nematode trophic composition. These findings suggest that a multiple scale analysis based on a nested sampling design could significantly improve our knowledge of bathymetric patterns of deep-sea biodiversity and its drivers.

Collaboration During the NASA ABoVE Airborne SAR Campaign: Sampling Strategies Used by NGEE Arctic and Other Partners in Alaska and Western Canada

NASA Astrophysics Data System (ADS)

Wullschleger, S. D.; Charsley-Groffman, L.; Baltzer, J. L.; Berg, A. A.; Griffith, P. C.; Jafarov, E. E.; Marsh, P.; Miller, C. E.; Schaefer, K. M.; Siqueira, P.; Wilson, C. J.; Kasischke, E. S.

2017-12-01

There is considerable interest in using L- and P-band Synthetic Aperture Radar (SAR) data to monitor variations in aboveground woody biomass, soil moisture, and permafrost conditions in high-latitude ecosystems. Such information is useful for quantifying spatial heterogeneity in surface and subsurface properties, and for model development and evaluation. To conduct these studies, it is desirable that field studies share a common sampling strategy so that the data from multiple sites can be combined and used to analyze variations in conditions across different landscape geomorphologies and vegetation types. In 2015, NASA launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE) to study the sensitivity and resilience of these ecosystems to disturbance and environmental change. NASA is able to leverage its remote sensing strengths to collect airborne and satellite observations to capture important ecosystem properties and dynamics across large spatial scales. A critical component of this effort includes collection of ground-based data that can be used to analyze, calibrate and validate remote sensing products. ABoVE researchers at a large number of sites located in important Arctic and boreal ecosystems in Alaska and western Canada are following common design protocols and strategies for measuring soil moisture, thaw depth, biomass, and wetland inundation. Here we elaborate on those sampling strategies as used in the 2017 summer SAR campaign and address the sampling design and measurement protocols for supporting the ABoVE aerial activities. Plot size, transect length, and distribution of replicates across the landscape systematically allowed investigators to optimally sample a site for soil moisture, thaw depth, and organic layer thickness. Specific examples and data sets are described for the Department of Energy's Next-Generation Ecosystem Experiments (NGEE Arctic) project field sites near Nome and Barrow, Alaska. Future airborne and satellite campaigns will be conducted by the NASA ABoVE team and additional collaboration is encouraged.

Impact of uneven sample morphology on mass resolving power in linear MALDI-TOF mass spectrometry: A comprehensive theoretical investigation.

PubMed

Cai, Yi-Hong; Wang, Yi-Sheng

2018-04-01

This work discusses the correlation between the mass resolving power of matrix-assisted laser desorption/ionization time-of-flight mass analyzers and extraction condition with an uneven sample morphology. Previous theoretical calculations show that the optimum extraction condition for flat samples involves an ideal ion source design and extraction delay. A general expression of spectral feature takes into account ion initial velocity, and extraction delay is derived in the current study. The new expression extends the comprehensive calculation to uneven sample surfaces and above 90% Maxell-Boltzmann initial velocity distribution of ions to account for imperfect ionization condition. Calculation shows that the impact of uneven sample surface or initial spatial spread of ions is negligible when the extraction delay is away from the ideal value. When the extraction delay approaches the optimum value, the flight-time topology shows a characteristic curve shape, and the time-domain mass spectral feature broadens with an increase in initial spatial spread of ions. For protonated 2,5-dihydroxybenzoic acid, the mass resolving power obtained from a sample of 3-μm surface roughness is approximately 3.3 times lower than that of flat samples. For ions of m/z 3000 coexpanded with 2,5-dihydroxybenzoic acid, the mass resolving power in the 3-μm surface roughness case only reduces roughly 7%. Comprehensive calculations also show that the mass resolving power of lighter ions is more sensitive to the accuracy of the extraction delay than heavier ions. Copyright © 2018 John Wiley & Sons, Ltd.

High Temporal and Spatial Resolution Coverage of Earth from Commercial AVSTAR Systems in Geostationary Orbit

NASA Astrophysics Data System (ADS)

Lecompte, M. A.; Heaps, J. F.; Williams, F. H.

Imaging the earth from Geostationary Earth Orbit (GEO) allows frequent updates of environmental conditions within an observable hemisphere at time and spatial scales appropriate to the most transient observable terrestrial phenomena. Coverage provided by current GEO Meteorological Satellites (METSATS) fails to fully exploit this advantage due primarily to obsolescent technology and also institutional inertia. With the full benefit of GEO based imaging unrealized, rapidly evolving phenomena, occurring at the smallest spatial and temporal scales that frequently have significant environmental impact remain unobserved. These phenomena may be precursors for the most destructive natural processes that adversely effect society. Timely distribution of information derived from "real-time" observations thus may provide opportunities to mitigate much of the damage to life and property that would otherwise occur. AstroVision International's AVStar Earth monitoring system is designed to overcome the current limitations if GEO Earth coverage and to provide real time monitoring of changes to the Earth's complete atmospheric, land and marine surface environments including fires, volcanic events, lightning and meteoritic events on a "live," true color, and multispectral basis. The understanding of severe storm dynamics and its coupling to the earth's electro-sphere will be greatly enhanced by observations at unprecedented sampling frequencies and spatial resolution. Better understanding of these natural phenomena and AVStar operational real-time coverage may also benefit society through improvements in severe weather prediction and warning. AstroVision's AVStar system, designed to provide this capability with the first of a constellation of GEO- based commercial environmental monitoring satellites to be launched in late 2003 will be discussed, including spatial and temporal resolution, spectral coverage with applications and an inventory of the potential benefits to society, science, commerce and education.

Bayesian hierarchical models for smoothing in two-phase studies, with application to small area estimation.

PubMed

Ross, Michelle; Wakefield, Jon

2015-10-01

Two-phase study designs are appealing since they allow for the oversampling of rare sub-populations which improves efficiency. In this paper we describe a Bayesian hierarchical model for the analysis of two-phase data. Such a model is particularly appealing in a spatial setting in which random effects are introduced to model between-area variability. In such a situation, one may be interested in estimating regression coefficients or, in the context of small area estimation, in reconstructing the population totals by strata. The efficiency gains of the two-phase sampling scheme are compared to standard approaches using 2011 birth data from the research triangle area of North Carolina. We show that the proposed method can overcome small sample difficulties and improve on existing techniques. We conclude that the two-phase design is an attractive approach for small area estimation.

The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments.

PubMed

Martins, Marina C M; Caldana, Camila; Wolf, Lucia Daniela; de Abreu, Luis Guilherme Furlan

2018-01-01

The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

Monitoring multiple species: Estimating state variables and exploring the efficacy of a monitoring program

USGS Publications Warehouse

Mattfeldt, S.D.; Bailey, L.L.; Grant, E.H.C.

2009-01-01

Monitoring programs have the potential to identify population declines and differentiate among the possible cause(s) of these declines. Recent criticisms regarding the design of monitoring programs have highlighted a failure to clearly state objectives and to address detectability and spatial sampling issues. Here, we incorporate these criticisms to design an efficient monitoring program whose goals are to determine environmental factors which influence the current distribution and measure change in distributions over time for a suite of amphibians. In designing the study we (1) specified a priori factors that may relate to occupancy, extinction, and colonization probabilities and (2) used the data collected (incorporating detectability) to address our scientific questions and adjust our sampling protocols. Our results highlight the role of wetland hydroperiod and other local covariates in the probability of amphibian occupancy. There was a change in overall occupancy probabilities for most species over the first three years of monitoring. Most colonization and extinction estimates were constant over time (years) and space (among wetlands), with one notable exception: local extinction probabilities for Rana clamitans were lower for wetlands with longer hydroperiods. We used information from the target system to generate scenarios of population change and gauge the ability of the current sampling to meet monitoring goals. Our results highlight the limitations of the current sampling design, emphasizing the need for long-term efforts, with periodic re-evaluation of the program in a framework that can inform management decisions.

Combined VIS-IR spectrometer with vertical probe beam

NASA Astrophysics Data System (ADS)

Protopopov, V.

2017-12-01

A prototype of a combined visible-infrared spectrometer with a vertical probe beam is designed and tested. The combined spectral range is 0.4-20 μ with spatial resolution 1 mm. Basic features include the ability to measure both visibly transparent and opaque substances, as well as buried structures, such as in semiconductor industry; horizontal orientation of a sample, including semiconductor wafers; and reflection mode of operation, delivering twice the sensitivity compared to the transmission mode.

Spatial information is processed even when it is task-irrelevant: implications for neuroimaging task design.

PubMed

Meegan, Daniel V; Honsberger, Michael J M

2005-05-01

Many neuroimaging studies have been designed to differentiate domain-specific processes in the brain. A common design constraint is to use identical stimuli for different domain-specific tasks. For example, an experiment investigating spatial versus identity processing would present compound spatial-identity stimuli in both spatial and identity tasks, and participants would be instructed to attend to, encode, maintain, or retrieve spatial information in the spatial task, and identity information in the identity task. An assumption in such studies is that spatial information will not be processed in the identity task, as it is irrelevant for that task. We report three experiments demonstrating violations of this assumption. Our results suggest that comparisons of spatial and identity tasks in existing neuroimaging studies have underestimated the amount of brain activation that is spatial-specific. For future neuroimaging studies, we recommend unique stimulus displays for each domain-specific task, and event-related measurement of post-stimulus processing.

On spatial coalescents with multiple mergers in two dimensions.

PubMed

Heuer, Benjamin; Sturm, Anja

2013-08-01

We consider the genealogy of a sample of individuals taken from a spatially structured population when the variance of the offspring distribution is relatively large. The space is structured into discrete sites of a graph G. If the population size at each site is large, spatial coalescents with multiple mergers, so called spatial Λ-coalescents, for which ancestral lines migrate in space and coalesce according to some Λ-coalescent mechanism, are shown to be appropriate approximations to the genealogy of a sample of individuals. We then consider as the graph G the two dimensional torus with side length 2L+1 and show that as L tends to infinity, and time is rescaled appropriately, the partition structure of spatial Λ-coalescents of individuals sampled far enough apart converges to the partition structure of a non-spatial Kingman coalescent. From a biological point of view this means that in certain circumstances both the spatial structure as well as larger variances of the underlying offspring distribution are harder to detect from the sample. However, supplemental simulations show that for moderately large L the different structure is still evident. Copyright © 2012 Elsevier Inc. All rights reserved.

Assessing map accuracy in a remotely sensed, ecoregion-scale cover map

USGS Publications Warehouse

Edwards, T.C.; Moisen, Gretchen G.; Cutler, D.R.

1998-01-01

Landscape- and ecoregion-based conservation efforts increasingly use a spatial component to organize data for analysis and interpretation. A challenge particular to remotely sensed cover maps generated from these efforts is how best to assess the accuracy of the cover maps, especially when they can exceed 1000 s/km2 in size. Here we develop and describe a methodological approach for assessing the accuracy of large-area cover maps, using as a test case the 21.9 million ha cover map developed for Utah Gap Analysis. As part of our design process, we first reviewed the effect of intracluster correlation and a simple cost function on the relative efficiency of cluster sample designs to simple random designs. Our design ultimately combined clustered and subsampled field data stratified by ecological modeling unit and accessibility (hereafter a mixed design). We next outline estimation formulas for simple map accuracy measures under our mixed design and report results for eight major cover types and the three ecoregions mapped as part of the Utah Gap Analysis. Overall accuracy of the map was 83.2% (SE=1.4). Within ecoregions, accuracy ranged from 78.9% to 85.0%. Accuracy by cover type varied, ranging from a low of 50.4% for barren to a high of 90.6% for man modified. In addition, we examined gains in efficiency of our mixed design compared with a simple random sample approach. In regard to precision, our mixed design was more precise than a simple random design, given fixed sample costs. We close with a discussion of the logistical constraints facing attempts to assess the accuracy of large-area, remotely sensed cover maps.

High spatial and temporal resolution cell manipulation techniques in microchannels.

PubMed

Novo, Pedro; Dell'Aica, Margherita; Janasek, Dirk; Zahedi, René P

2016-03-21

The advent of microfluidics has enabled thorough control of cell manipulation experiments in so called lab on chips. Lab on chips foster the integration of actuation and detection systems, and require minute sample and reagent amounts. Typically employed microfluidic structures have similar dimensions as cells, enabling precise spatial and temporal control of individual cells and their local environments. Several strategies for high spatio-temporal control of cells in microfluidics have been reported in recent years, namely methods relying on careful design of the microfluidic structures (e.g. pinched flow), by integration of actuators (e.g. electrodes or magnets for dielectro-, acousto- and magneto-phoresis), or integrations thereof. This review presents the recent developments of cell experiments in microfluidics divided into two parts: an introduction to spatial control of cells in microchannels followed by special emphasis in the high temporal control of cell-stimulus reaction and quenching. In the end, the present state of the art is discussed in line with future perspectives and challenges for translating these devices into routine applications.

Greater loss of object than spatial mnemonic discrimination in aged adults.

PubMed

Reagh, Zachariah M; Ho, Huy D; Leal, Stephanie L; Noche, Jessica A; Chun, Amanda; Murray, Elizabeth A; Yassa, Michael A

2016-04-01

Previous studies across species have established that the aging process adversely affects certain memory-related brain regions earlier than others. Behavioral tasks targeted at the function of vulnerable regions can provide noninvasive methods for assessing the integrity of particular components of memory throughout the lifespan. The present study modified a previous task designed to separately but concurrently test detailed memory for object identity and spatial location. Memory for objects or items is thought to rely on perirhinal and lateral entorhinal cortices, among the first targets of Alzheimer's related neurodegeneration. In line with prior work, we split an aged adult sample into "impaired" and "unimpaired" groups on the basis of a standardized word-learning task. The "impaired" group showed widespread difficulty with memory discrimination, whereas the "unimpaired" group showed difficulty with object, but not spatial memory discrimination. These findings support the hypothesized greater age-related impacts on memory for objects or items in older adults, perhaps even with healthy aging. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Consistent patterns of variation in macrobenthic assemblages and environmental variables over multiple spatial scales using taxonomic and functional approaches.

PubMed

Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos

2016-09-01

Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

Mapping soil landscape as spatial continua: The Neural Network Approach

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing

2000-03-01

A neural network approach was developed to populate a soil similarity model that was designed to represent soil landscape as spatial continua for hydroecological modeling at watersheds of mesoscale size. The approach employs multilayer feed forward neural networks. The input to the network was data on a set of soil formative environmental factors; the output from the network was a set of similarity values to a set of prescribed soil classes. The network was trained using a conjugate gradient algorithm in combination with a simulated annealing technique to learn the relationships between a set of prescribed soils and their environmental factors. Once trained, the network was used to compute for every location in an area the similarity values of the soil to the set of prescribed soil classes. The similarity values were then used to produce detailed soil spatial information. The approach also included a Geographic Information System procedure for selecting representative training and testing samples and a process of determining the network internal structure. The approach was applied to soil mapping in a watershed, the Lubrecht Experimental Forest, in western Montana. The case study showed that the soil spatial information derived using the neural network approach reveals much greater spatial detail and has a higher quality than that derived from the conventional soil map. Implications of this detailed soil spatial information for hydroecological modeling at the watershed scale are also discussed.

Spatial-temporal variability of soil water content in a cropland-shelterbelt-desert site in an arid inland river basin of Northwest China

NASA Astrophysics Data System (ADS)

Shen, Qin; Gao, Guangyao; Hu, Wei; Fu, Bojie

2016-09-01

Knowledge of the spatial-temporal variability of soil water content (SWC) is critical for understanding a range of hydrological processes. In this study, the spatial variance and temporal stability of SWC were investigated in a cropland-shelterbelt-desert site at the oasis-desert ecotone in the middle of the Heihe River Basin, China. The SWC was measured on 65 occasions to a depth of 2.8 m at 45 locations during two growing seasons from 2012 to 2013. The standard deviation of the SWC versus the mean SWC exhibited a convex upward relationship in the shelterbelt with the greatest spatial variation at the SWC of around 22.0%, whereas a linearly increasing relationship was observed for the cropland, desert, and land use pattern. The standard deviation of the relative difference was positively linearly correlated with the SWC (p < 0.05) for the land use pattern, whereas such a relationship was not found in the three land use types. The spatial pattern of the SWC was more time stable for the land use pattern, followed by desert, shelterbelt, and cropland. The spatial pattern of SWC changed dramatically among different soil layers. The locations representing the mean SWC varied with the depth, and no location could represent the whole soil profile due to different soil texture, root distribution and irrigation management. The representative locations of each soil layer could be used to estimate the mean SWC well. The statistics of temporal stability of the SWC could be presented equally well with a low frequency of observation (30-day interval) as with a high frequency (5-day interval). Sampling frequency had little effect on the selection of the representative locations of the field mean SWC. This study provides useful information for designing the optimal strategy for sampling SWC at the oasis-desert ecotone in the arid inland river basin.

A simple homogeneous model for regular and irregular metallic wire media samples

NASA Astrophysics Data System (ADS)

Kosulnikov, S. Y.; Mirmoosa, M. S.; Simovski, C. R.

2018-02-01

To simplify the solution of electromagnetic problems with wire media samples, it is reasonable to treat them as the samples of a homogeneous material without spatial dispersion. The account of spatial dispersion implies additional boundary conditions and makes the solution of boundary problems difficult especially if the sample is not an infinitely extended layer. Moreover, for a novel type of wire media - arrays of randomly tilted wires - a spatially dispersive model has not been developed. Here, we introduce a simplistic heuristic model of wire media samples shaped as bricks. Our model covers WM of both regularly and irregularly stretched wires.

The study of combining Latin Hypercube Sampling method and LU decomposition method (LULHS method) for constructing spatial random field

NASA Astrophysics Data System (ADS)

WANG, P. T.

2015-12-01

Groundwater modeling requires to assign hydrogeological properties to every numerical grid. Due to the lack of detailed information and the inherent spatial heterogeneity, geological properties can be treated as random variables. Hydrogeological property is assumed to be a multivariate distribution with spatial correlations. By sampling random numbers from a given statistical distribution and assigning a value to each grid, a random field for modeling can be completed. Therefore, statistics sampling plays an important role in the efficiency of modeling procedure. Latin Hypercube Sampling (LHS) is a stratified random sampling procedure that provides an efficient way to sample variables from their multivariate distributions. This study combines the the stratified random procedure from LHS and the simulation by using LU decomposition to form LULHS. Both conditional and unconditional simulations of LULHS were develpoed. The simulation efficiency and spatial correlation of LULHS are compared to the other three different simulation methods. The results show that for the conditional simulation and unconditional simulation, LULHS method is more efficient in terms of computational effort. Less realizations are required to achieve the required statistical accuracy and spatial correlation.

Nondestructive Superresolution Imaging of Defects and Nonuniformities in Metals, Semiconductors, Dielectrics, Composites, and Plants Using Evanescent Microwaves

NASA Technical Reports Server (NTRS)

Tabib-Azar, M.; Pathak, P. S.; Ponchak, G.; LeClair, S.

1999-01-01

We have imaged and mapped material nonuniformities and defects using microwaves generated at the end of a microstripline resonator with 0.4 micrometer lateral spatial resolution at 1 GHz. Here we experimentally examine the effect of microstripline substrate permittivity, the feedline-to-resonator coupling strength, and probe tip geometry on the spatial resolution of the probe. Carbon composites, dielectrics, semiconductors, metals, and botanical samples were scanned for defects, residual stresses, subsurface features, areas of different film thickness, and moisture content. The resulting evanescent microwave probe (EMP) images are discussed. The main objective of this work is to demonstrate the overall capabilities of the EMP imaging technique as well as to discuss various probe parameters that can be used to design EMPs for different applications.

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

PubMed

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

Feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory.

PubMed

Wang, Haoyu; Miao, Yanwei; Zhou, Kun; Yu, Yanming; Bao, Shanglian; He, Qiang; Dai, Yongming; Xuan, Stephanie Y; Tarabishy, Bisher; Ye, Yongquan; Hu, Jiani

2010-09-01

To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.

Decision-theoretic approach to data acquisition for transit operations planning

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

Ritchie, S.G.

The most costly element of transportation planning and modeling activities in the past has usually been that of data acquisition. This is even truer today when the unit costs of data collection are increasing rapidly and at the same time budgets are severely limited by continuing policies of fiscal austerity in the public sector. The overall objectives of this research were to improve the decisions and decision-making capabilities of transit operators or planners in short-range transit planning, and to improve the quality and cost-effectiveness of associated route or corridor-level data collection and service monitoring activities. A new approach was presentedmore » for sequentially updating the parameters of both simple and multiple linear regression models with stochastic regressors, and for determining the expected value of sample information and expected net gain of sampling for associated sample designs. A new approach was also presented for estimating and updating (both spatially and temporally) the parameters of multinomial logit discrete choice models, and for determining associated optimal sample designs for attribute-based and choice-based sampling methods. The approach provides an effective framework for addressing the issue of optimal sampling method and sample size, which to date have been largely unresolved. The application of these methodologies and the feasibility of the decision-theoretic approach was illustrated with a hypothetical case study example.« less

Spatial distributions of the red palm mite, Raoiella indica (Acari: Tenuipalpidae) on coconut and their implications for development of efficient sampling plans.

PubMed

Roda, A; Nachman, G; Hosein, F; Rodrigues, J C V; Peña, J E

2012-08-01

The red palm mite (Raoiella indica), an invasive pest of coconut, entered the Western hemisphere in 2004, then rapidly spread through the Caribbean and into Florida, USA. Developing effective sampling methods may aid in the timely detection of the pest in a new area. Studies were conducted to provide and compare intra tree spatial distribution of red palm mite populations on coconut in two different geographical areas, Trinidad and Puerto Rico, recently invaded by the mite. The middle stratum of a palm hosted significantly more mites than fronds from the upper or lower canopy and fronds from the lower stratum, on average, had significantly fewer mites than the two other strata. The mite populations did not vary within a frond. Mite densities on the top section of the pinna had significantly lower mite densities than the two other sections, which were not significantly different from each other. In order to improve future sampling plans for the red palm mite, the data was used to estimate the variance components associated with the various levels of the hierarchical sampling design. Additionally, presence-absence data were used to investigate the probability of no mites being present in a pinna section randomly chosen from a frond inhabited by mites at a certain density. Our results show that the most precise density estimate at the plantation level is to sample one pinna section per tree from as many trees as possible.

Developing effective sampling designs for monitoring natural resources in Alaskan national parks: an example using simulations and vegetation data

USGS Publications Warehouse

Thompson, William L.; Miller, Amy E.; Mortenson, Dorothy C.; Woodward, Andrea

2011-01-01

Monitoring natural resources in Alaskan national parks is challenging because of their remoteness, limited accessibility, and high sampling costs. We describe an iterative, three-phased process for developing sampling designs based on our efforts to establish a vegetation monitoring program in southwest Alaska. In the first phase, we defined a sampling frame based on land ownership and specific vegetated habitats within the park boundaries and used Path Distance analysis tools to create a GIS layer that delineated portions of each park that could be feasibly accessed for ground sampling. In the second phase, we used simulations based on landcover maps to identify size and configuration of the ground sampling units (single plots or grids of plots) and to refine areas to be potentially sampled. In the third phase, we used a second set of simulations to estimate sample size and sampling frequency required to have a reasonable chance of detecting a minimum trend in vegetation cover for a specified time period and level of statistical confidence. Results of the first set of simulations indicated that a spatially balanced random sample of single plots from the most common landcover types yielded the most efficient sampling scheme. Results of the second set of simulations were compared with field data and indicated that we should be able to detect at least a 25% change in vegetation attributes over 31. years by sampling 8 or more plots per year every five years in focal landcover types. This approach would be especially useful in situations where ground sampling is restricted by access.

Monitoring and evaluating the impact of national school-based deworming in Kenya: study design and baseline results.

PubMed

Mwandawiro, Charles S; Nikolay, Birgit; Kihara, Jimmy H; Ozier, Owen; Mukoko, Dunstan A; Mwanje, Mariam T; Hakobyan, Anna; Pullan, Rachel L; Brooker, Simon J; Njenga, Sammy M

2013-07-05

An increasing number of countries in Africa and elsewhere are developing national plans for the control of neglected tropical diseases. A key component of such plans is school-based deworming (SBD) for the control of soil-transmitted helminths (STHs) and schistosomiasis. Monitoring and evaluation (M&E) of national programmes is essential to ensure they are achieving their stated aims and to evaluate when to reduce the frequency of treatment or when to halt it altogether. The article describes the M&E design of the Kenya national SBD programme and presents results from the baseline survey conducted in early 2012. The M&E design involves a stratified series of pre- and post-intervention, repeat cross-sectional surveys in a representative sample of 200 schools (over 20,000 children) across Kenya. Schools were sampled based on previous knowledge of STH endemicity and were proportional to population size. Stool (and where relevant urine) samples were obtained for microscopic examination and in a subset of schools; finger-prick blood samples were collected to estimate haemoglobin concentration. Descriptive and spatial analyses were conducted. The evaluation measured both prevalence and intensity of infection. Overall, 32.4% of children were infected with at least one STH species, with Ascaris lumbricoides as the most common species detected. The overall prevalence of Schistosoma mansoni was 2.1%, while in the Coast Province the prevalence of S. haematobium was 14.8%. There was marked geographical variation in the prevalence of species infection at school, district and province levels. The prevalence of hookworm infection was highest in Western Province (25.1%), while A. lumbricoides and T. trichiura prevalence was highest in the Rift Valley (27.1% and 11.9%). The lowest prevalence was observed in the Rift Valley for hookworm (3.5%), in the Coast for A. lumbricoides (1.0%), and in Nyanza for T. trichiura (3.6%). The prevalence of S. mansoni was most common in Western Province (4.1%). The current findings are consistent with the known spatial ecology of STH and schistosome infections and provide an important empirical basis on which to evaluate the impact of regular mass treatment through the school system in Kenya.

Design and realization of tourism spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Ma, Zhangbao; Qi, Qingwen; Xu, Li

2008-10-01

In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

Design and Compilation of a Geodatabase of Existing Salinity Information for the Rio Grande Basin, from the Rio Arriba-Sandoval County Line, New Mexico, to Presidio, Texas, 2010

USGS Publications Warehouse

Shah, Sachin D.; Maltby, David R.

2010-01-01

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, compiled salinity-related water-quality data and information in a geodatabase containing more than 6,000 sampling sites. The geodatabase was designed as a tool for water-resource management and includes readily available digital data sources from the U.S. Geological Survey, U.S. Environmental Protection Agency, New Mexico Interstate Stream Commission, Sustainability of semi-Arid Hydrology and Riparian Areas, Paso del Norte Watershed Council, numerous other State and local databases, and selected databases maintained by the University of Arizona and New Mexico State University. Salinity information was compiled for an approximately 26,000-square-mile area of the Rio Grande Basin from the Rio Arriba-Sandoval County line, New Mexico, to Presidio, Texas. The geodatabase relates the spatial location of sampling sites with salinity-related water-quality data reported by multiple agencies. The sampling sites are stored in a geodatabase feature class; each site is linked by a relationship class to the corresponding sample and results stored in data tables.

Visual sensitivity to spatially sampled modulation in human observers

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.; Macleod, Donald I. A.

1991-01-01

Thresholds were measured for detecting spatial luminance modulation in regular lattices of visually discrete dots. Thresholds for modulation of a lattice are generally higher than the corresponding threshold for modulation of a continuous field, and the size of the threshold elevation, which depends on the spacing of the lattice elements, can be as large as a one log unit. The largest threshold elevations are seen when the sample spacing is 12 min arc or greater. Theories based on response compression cannot explain the further observation that the threshold elevations due to spatial sampling are also dependent on modulation frequency: the greatest elevations occur with higher modulation frequencies. The idea that this is due to masking of the modulation frequency by the spatial frequencies in the sampling lattice is considered.

Optimization of Apparatus Design and Behavioral Measures for the Assessment of Visuo-Spatial Learning and Memory of Mice on the Barnes Maze

ERIC Educational Resources Information Center

O'Leary, Timothy P.; Brown, Richard E.

2013-01-01

We have previously shown that apparatus design can affect visual-spatial cue use and memory performance of mice on the Barnes maze. The present experiment extends these findings by determining the optimal behavioral measures and test procedure for analyzing visuo-spatial learning and memory in three different Barnes maze designs. Male and female…

ODM2 (Observation Data Model): The EarthChem Use Case

NASA Astrophysics Data System (ADS)

Lehnert, Kerstin; Song, Lulin; Hsu, Leslie; Horsburgh, Jeffrey S.; Aufdenkampe, Anthony K.; Mayorga, Emilio; Tarboton, David; Zaslavsky, Ilya

2014-05-01

PetDB is an online data system that was created in the late 1990's to serve online a synthesis of published geochemical and petrological data of igneous and metamorphic rocks. PetDB has today reached a volume of 2.5 million analytical values for nearly 70,000 rock samples. PetDB's data model (Lehnert et al., G-Cubed 2000) was designed to store sample-based observational data generated by the analysis of rocks, together with a wide range of metadata documenting provenance of the samples, analytical procedures, data quality, and data source. Attempts to store additional types of geochemical data such as time-series data of seafloor hydrothermal springs and volcanic gases, depth-series data for marine sediments and soils, and mineral or mineral inclusion data revealed the limitations of the schema: the inability to properly record sample hierarchies (for example, a garnet that is included in a diamond that is included in a xenolith that is included in a kimberlite rock sample), inability to properly store time-series data, inability to accommodate classification schemes other than rock lithologies, deficiencies of identifying and documenting datasets that are not part of publications. In order to overcome these deficiencies, PetDB has been developing a new data schema using the ODM2 information model (ODM=Observation Data Model). The development of ODM2 is a collaborative project that leverages the experience of several existing information representations, including PetDB and EarthChem, and the CUAHSI HIS Observations Data Model (ODM), as well as the general specification for encoding observational data called Observations and Measurements (O&M) to develop a uniform information model that seamlessly manages spatially discrete, feature-based earth observations from environmental samples and sample fractions as well as in-situ sensors, and to test its initial implementation in a variety of user scenarios. The O&M model, adopted as an international standard by the Open Geospatial Consortium, and later by ISO, is the foundation of several domain markup languages such as OGC WaterML 2, used for exchanging hydrologic time series. O&M profiles for samples and sample fractions have not been standardized yet, and there is a significant variety in sample data representations used across agencies and academic projects. The intent of the ODM2 project is to create a unified relational representation for different types of spatially discrete observational data, ensuring that the data can be efficiently stored, transferred, catalogued and queried within a variety of earth science applications. We will report on the initial design and implementation of the new model for PetDB, and results of testing the model against a set of common queries. We have explored several aspects of the model, including: semantic consistency, validation and integrity checking, portability and maintainability, query efficiency, and scalability. The sample datasets from PetDB have been loaded in the initial physical implementation for testing. The results of the experiments point to both benefits and challenges of the initial design, and illustrate the key trade-off between the generality of design, ease of interpretation, and query efficiency, especially as the system needs to scale to millions of records.

Engineering Play: Exploring Associations with Executive Function, Mathematical Ability, and Spatial Ability in Preschool

NASA Astrophysics Data System (ADS)

Gold, Zachary Samuel

Engineering play is a new perspective on preschool education that views constructive play as an engineering design process that parallels the way engineers think and work when they develop engineered solutions to human problems (Bairaktarova, Evangelou, Bagiati, & Brophy, 2011). Early research from this perspective supports its use in framing play as a key learning context. However, no research to date has examined associations between engineering play and other factors linked with early school success, such as executive function, mathematical ability, and spatial ability. Additionally, more research is needed to further validate a new engineering play observational measure. This study had two main goals: (1) to gather early validity data on the engineering play measure as a potentially useful instrument for documenting the occurrence of children's engineering play behaviors in educational contexts, such as block play. This was done by testing the factor structure of the engineering play behaviors in this sample and their association with preschoolers' planning, a key aspect of the engineering design process; (2) to explore associations between preschoolers' engineering play and executive function, mathematical ability, and spatial ability. Participants included 110 preschoolers (62 girls; 48 boys; M = 58.47 months) from 10 classrooms in the Midwest United States coded for their frequency of engagement in each of the nine engineering play behaviors. A confirmatory factor analysis resulted in one engineering play factor including six of the engineering play behaviors. A series of marginal regression models revealed that the engineering play factor was significantly and positively associated with the spatial horizontal rotation transformation. However, engineering play was not significantly related to planning ability, executive function, informal mathematical abilities, or other spatial transformation skills. Follow-up analyses revealed significant positive associations between engineering play and planning, executive function, and geometry for only a subgroup of children (n = 27) who had individualized education program (IEP) status. This was the first of a series of studies planned to evaluate the potential of the engineering play perspective as a tool for understanding young children's development and learning across multiple developmental domains. Although most hypotheses regarding engineering play and cognitive skills were not supported, the study provided partial evidence for the reliability and validity of the engineering play observation measure. Future research should include larger sample sizes with more statistical power, continued refinement of the engineering play observation measure, examination of potential associations with specific early learning domains, including spatial ability and language, and more comparisons of engineering play between typically developing children and children with disabilities.

Designs of Optoelectronic Trinary Signed-Digit Multiplication by use of Joint Spatial Encodings and Optical Correlation

NASA Astrophysics Data System (ADS)

Cherri, Abdallah K.

1999-02-01

Trinary signed-digit (TSD) symbolic-substitution-based (SS-based) optical adders, which were recently proposed, are used as the basic modules for designing highly parallel optical multiplications by use of cascaded optical correlators. The proposed multiplications perform carry-free generation of the multiplication partial products of two words in constant time. Also, three different multiplication designs are presented, and new joint spatial encodings for the TSD numbers are introduced. The proposed joint spatial encodings allow one to reduce the SS computation rules involved in optical multiplication. In addition, the proposed joint spatial encodings increase the space bandwidth product of the spatial light modulators of the optical system. This increase is achieved by reduction of the numbers of pixels in the joint spatial encodings for the input TSD operands as well as reduction of the number of pixels used in the proposed matched spatial filters for the optical multipliers.

Designs of optoelectronic trinary signed-digit multiplication by use of joint spatial encodings and optical correlation.

PubMed

Cherri, A K

1999-02-10

Trinary signed-digit (TSD) symbolic-substitution-based (SS-based) optical adders, which were recently proposed, are used as the basic modules for designing highly parallel optical multiplications by use of cascaded optical correlators. The proposed multiplications perform carry-free generation of the multiplication partial products of two words in constant time. Also, three different multiplication designs are presented, and new joint spatial encodings for the TSD numbers are introduced. The proposed joint spatial encodings allow one to reduce the SS computation rules involved in optical multiplication. In addition, the proposed joint spatial encodings increase the space-bandwidth product of the spatial light modulators of the optical system. This increase is achieved by reduction of the numbers of pixels in the joint spatial encodings for the input TSD operands as well as reduction of the number of pixels used in the proposed matched spatial filters for the optical multipliers.

Preferential sampling and Bayesian geostatistics: Statistical modeling and examples.

PubMed

Cecconi, Lorenzo; Grisotto, Laura; Catelan, Dolores; Lagazio, Corrado; Berrocal, Veronica; Biggeri, Annibale

2016-08-01

Preferential sampling refers to any situation in which the spatial process and the sampling locations are not stochastically independent. In this paper, we present two examples of geostatistical analysis in which the usual assumption of stochastic independence between the point process and the measurement process is violated. To account for preferential sampling, we specify a flexible and general Bayesian geostatistical model that includes a shared spatial random component. We apply the proposed model to two different case studies that allow us to highlight three different modeling and inferential aspects of geostatistical modeling under preferential sampling: (1) continuous or finite spatial sampling frame; (2) underlying causal model and relevant covariates; and (3) inferential goals related to mean prediction surface or prediction uncertainty. © The Author(s) 2016.

Precision Requirements for Space-based XCO2 Data

NASA Technical Reports Server (NTRS)

Miller, C. E.; Crisp, D.; DeCola, P. C.; Olsen, S. C.; Randerson, J. T.; Rayner, P.; Jacob, D.J.; Jones, D.; Suntharalingam, P.

2005-01-01

Precision requirements have been determined for the column-averaged CO2 dry air mole fraction (X(sub CO2)) data products to be delivered by the Orbiting Carbon Observatory (OCO). These requirements result from an assessment of the amplitude and spatial gradients in X(sub CO2), the relationship between X(sub CO2) precision and surface CO2 flux uncertainties calculated from inversions of the X(sub CO2) data, and the effects of X,,Z biases on CO2 flux inversions. Observing system simulation experiments and synthesis inversion modeling demonstrate that the OCO mission design and sampling strategy provide the means to achieve the X(sub CO2) precision requirements. The impact of X(sub CO2) biases on CO2 flux uncertainties depend on their spatial and temporal extent since CO2 sources and sinks are inferred from regional-scale X(sub CO2) gradients. Simulated OCO sampling of the TRACE-P CO2 fields shows the ability of X(sub CO2) data to constrain CO2 flux inversions over Asia and distinguish regional fluxes from India and China.

Evaluation of Heterogeneous Metabolic Profile in an Orthotopic Human Glioblastoma Xenograft Model Using Compressed Sensing Hyperpolarized 3D 13C Magnetic Resonance Spectroscopic Imaging

PubMed Central

Park, Ilwoo; Hu, Simon; Bok, Robert; Ozawa, Tomoko; Ito, Motokazu; Mukherjee, Joydeep; Phillips, Joanna J.; James, C. David; Pieper, Russell O.; Ronen, Sabrina M.; Vigneron, Daniel B.; Nelson, Sarah J.

2013-01-01

High resolution compressed sensing hyperpolarized 13C magnetic resonance spectroscopic imaging was applied in orthotopic human glioblastoma xenografts for quantitative assessment of spatial variations in 13C metabolic profiles and comparison with histopathology. A new compressed sensing sampling design with a factor of 3.72 acceleration was implemented to enable a factor of 4 increase in spatial resolution. Compressed sensing 3D 13C magnetic resonance spectroscopic imaging data were acquired from a phantom and 10 tumor-bearing rats following injection of hyperpolarized [1-13C]-pyruvate using a 3T scanner. The 13C metabolic profiles were compared with hematoxylin and eosin staining and carbonic anhydrase 9 staining. The high-resolution compressed sensing 13C magnetic resonance spectroscopic imaging data enabled the differentiation of distinct 13C metabolite patterns within abnormal tissues with high specificity in similar scan times compared to the fully sampled method. The results from pathology confirmed the different characteristics of 13C metabolic profiles between viable, non-necrotic, nonhypoxic tumor, and necrotic, hypoxic tissue. PMID:22851374

Evaluation of heterogeneous metabolic profile in an orthotopic human glioblastoma xenograft model using compressed sensing hyperpolarized 3D 13C magnetic resonance spectroscopic imaging.

PubMed

Park, Ilwoo; Hu, Simon; Bok, Robert; Ozawa, Tomoko; Ito, Motokazu; Mukherjee, Joydeep; Phillips, Joanna J; James, C David; Pieper, Russell O; Ronen, Sabrina M; Vigneron, Daniel B; Nelson, Sarah J

2013-07-01

High resolution compressed sensing hyperpolarized (13)C magnetic resonance spectroscopic imaging was applied in orthotopic human glioblastoma xenografts for quantitative assessment of spatial variations in (13)C metabolic profiles and comparison with histopathology. A new compressed sensing sampling design with a factor of 3.72 acceleration was implemented to enable a factor of 4 increase in spatial resolution. Compressed sensing 3D (13)C magnetic resonance spectroscopic imaging data were acquired from a phantom and 10 tumor-bearing rats following injection of hyperpolarized [1-(13)C]-pyruvate using a 3T scanner. The (13)C metabolic profiles were compared with hematoxylin and eosin staining and carbonic anhydrase 9 staining. The high-resolution compressed sensing (13)C magnetic resonance spectroscopic imaging data enabled the differentiation of distinct (13)C metabolite patterns within abnormal tissues with high specificity in similar scan times compared to the fully sampled method. The results from pathology confirmed the different characteristics of (13)C metabolic profiles between viable, non-necrotic, nonhypoxic tumor, and necrotic, hypoxic tissue. Copyright © 2012 Wiley Periodicals, Inc.

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

Adams, B.W.; et al.

The Large Area Picosecond PhotoDetector (LAPPD) Collaboration was formed in 2009 to develop large-area photodetectors capable of time resolutions measured in pico-seconds, with accompanying sub-millimeter spatial resolution. During the next three and one-half years the Collaboration developed the LAPPD design of 20 x 20 cm modules with gains greater thanmore » $10^7$ and non-uniformity less than $$15\\%$$, time resolution less than 50 psec for single photons and spatial resolution of 700~microns in both lateral dimensions. We describe the R\\&D performed to develop large-area micro-channel plate glass substrates, resistive and secondary-emitting coatings, large-area bialkali photocathodes, and RF-capable hermetic packaging. In addition, the Collaboration developed the necessary electronics for large systems capable of precise timing, built up from a custom low-power 15-GigaSample/sec waveform sampling 6-channel integrated circuit and supported by a two-level modular data acquisition system based on Field-Programmable Gate Arrays for local control, data-sparcification, and triggering. We discuss the formation, organization, and technical successes and short-comings of the Collaboration. The Collaboration ended in December 2012 with a transition from R\\&D to commercialization.« less

New designs for portable Raman instrumentation in defense applications

NASA Astrophysics Data System (ADS)

Carron, Keith; Ray, Bryan; Buller, Shane; Strickland, Aaron

2016-05-01

The realization of global terrorism after the September 11 attacks led immediately to a need for rapid field analysis of materials. Colorimetric test kits existed, but they are very subjective to interpret and they require contact with the sample. A push for handheld spectrometers quickly led to FTIR systems with ATR sampling, handheld IMS systems, and handheld Raman spectrometers. No single technique solves all of the problems of field detection. We will discuss the development of Raman instrumentation and, in particular, cover the advantages and the problems that are inherent in Raman portability. Portable Raman instrumentation began with a limited number of accessories: a point-and-shoot and some sort of vial adaptor. Currently this has expanded to stand-off attachments for measurements at a distance, air sampling to look for toxic gasses or aerosols, Orbital Raster Scan (ORS) to spatially average over samples, SERS attachments for trace detection, and fiber optic probes.

Geochemical surveys in the United States in relation to health.

USGS Publications Warehouse

Tourtelot, H.A.

1979-01-01

Geochemical surveys in relation to health may be classified as having one, two or three dimensions. One-dimensional surveys examine relations between concentrations of elements such as Pb in soils and other media and burdens of the same elements in humans, at a given time. The spatial distributions of element concentrations are not investigated. The primary objective of two-dimensional surveys is to map the distributions of element concentrations, commonly according to stratified random sampling designs based on either conceptual landscape units or artificial sampling strata, but systematic sampling intervals have also been used. Political units have defined sample areas that coincide with the units used to accumulate epidemiological data. Element concentrations affected by point sources have also been mapped. Background values, location of natural or technological anomalies and the geographic scale of variation for several elements often are determined. Three-dimensional surveys result when two-dimensional surveys are repeated to detect environmental changes. -Author

Approach for environmental baseline water sampling

USGS Publications Warehouse

Smith, K.S.

2011-01-01

Samples collected during the exploration phase of mining represent baseline conditions at the site. As such, they can be very important in forecasting potential environmental impacts should mining proceed, and can become measurements against which future changes are compared. Constituents in stream water draining mined and mineralized areas tend to be geochemically, spatially, and temporally variable, which presents challenges in collecting both exploration and baseline water-quality samples. Because short-term (daily) variations can complicate long-term trends, it is important to consider recent findings concerning geochemical variability of stream-water constituents at short-term timescales in designing sampling plans. Also, adequate water-quality information is key to forecasting potential ecological impacts from mining. Therefore, it is useful to collect baseline water samples adequate tor geochemical and toxicological modeling. This requires complete chemical analyses of dissolved constituents that include major and minor chemical elements as well as physicochemical properties (including pH, specific conductance, dissolved oxygen) and dissolved organic carbon. Applying chemical-equilibrium and appropriate toxicological models to water-quality information leads to an understanding of the speciation, transport, sequestration, bioavailability, and aquatic toxicity of potential contaminants. Insights gained from geochemical and toxicological modeling of water-quality data can be used to design appropriate mitigation and for economic planning for future mining activities.

Investigating phenology of larval fishes in St. Louis River ...

EPA Pesticide Factsheets

As part of the development of an early detection monitoring strategy for non-native fishes, larval fish surveys have been conducted since 2012 in the St. Louis River estuary. Survey data demonstrates there is considerable variability in fish abundance and species assemblages across different habitats and at multiple temporal scales. To optimize early detection monitoring we need to understand temporal and spatial patterns of larval fishes related to their development and dispersion, as well as the environmental factors that influence them. In 2016 we designed an experiment to assess the phenological variability in larval fish abundance and assemblages amongst shallow water habitats. Specifically, we sought to contrast different thermal environments and turbidity levels, as well as assess the importance of vegetation in these habitats. To evaluate phenological differences we sampled larval fish bi-weekly at nine locations from mid-May to mid-July. Sampling locations were split between upper estuary and lower estuary to contrast river versus seiche influenced habitats. To assess differences in thermal environments, temperature was monitored every 15 minutes at each sampling location throughout the study, beginning in early April. Our design also included sampling at both vegetated (or pre-vegetated) and non-vegetated stations within each sampling location throughout the study to assess the importance of this habitat variable. Hydroacoustic surveys (Biosonics) were

Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport

USGS Publications Warehouse

Marineau, Mathieu D.; Minear, J. Toby; Wright, Scott A.

2015-01-01

Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial variability in transport was also detected in the longitudinal profiles audibly and using signal processing algorithms. These experiments demonstrate the ability of hydrophone technology to capture the temporal and spatial variability of sediment transport, which may be missed when samples are collected using conventional methods.

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

Structure and biodiversity of coralligenous assemblages dominated by the precious red coral Corallium rubrum over broad spatial scales

PubMed Central

Casas-Güell, Edgar; Cebrian, Emma; Garrabou, Joaquim; Ledoux, Jean-Baptiste; Linares, Cristina; Teixidó, Núria

2016-01-01

Data on species diversity and structure in coralligenous outcrops dominated by Corallium rubrum are lacking. A hierarchical sampling including 3 localities and 9 sites covering more than 400 km of rocky coasts in NW Mediterranean, was designed to characterize the spatial variability of structure, composition and diversity of perennial species inhabiting coralligenous outcrops. We estimated species/taxa composition and abundance. Eight morpho-functional groups were defined according to their life span and growth to characterize the structural complexity of the outcrops. The species composition and structural complexity differed consistently across all spatial scales considered. The lowest and the highest variability were found among localities (separated by >200 km) and within sites (separated by 1–5 km), respectively supporting differences in diversity indices. The morpho-functional groups displayed a consistent spatial arrangement in terms of the number, size and shape of patches across study sites. These results contribute to filling the gap on the understanding of assemblage composition and structure and to build baselines to assess the response of this of this highly threatened habitat to anthropogenic disturbances. PMID:27857209

Prospects and pitfalls of occupational hazard mapping: 'between these lines there be dragons'.

PubMed

Koehler, Kirsten A; Volckens, John

2011-10-01

Hazard data mapping is a promising new technique that can enhance the process of occupational exposure assessment and risk communication. Hazard maps have the potential to improve worker health by providing key input for the design of hazard intervention and control strategies. Hazard maps are developed with aid from direct-reading instruments, which can collect highly spatially and temporally resolved data in a relatively short period of time. However, quantifying spatial-temporal variability in the occupational environment is not a straightforward process, and our lack of understanding of how to ascertain and model spatial and temporal variability is a limiting factor in the use and interpretation of workplace hazard maps. We provide an example of how sources of and exposures to workplace hazards may be mischaracterized in a hazard map due to a lack of completeness and representativeness of collected measurement data. Based on this example, we believe that a major priority for research in this emerging area should focus on the development of a statistical framework to quantify uncertainty in spatially and temporally varying data. In conjunction with this need is one for the development of guidelines and procedures for the proper sampling, generation, and evaluation of workplace hazard maps.

Development of an adaptive bilateral filter for evaluating color image difference

NASA Astrophysics Data System (ADS)

Wang, Zhaohui; Hardeberg, Jon Yngve

2012-04-01

Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

SEX DIFFERENCES ON THE WECHSLER INTELLIGENCE SCALE FOR CHILDREN-III IN BAHRAIN AND THE UNITED STATES.

PubMed

Bakhiet, Salaheldin Farah Attallah; Lynn, Richard

2015-12-01

Sex differences on the Wechsler Intelligence Scale for Children-III (WISC-III) are reported for children in Bahrain and the United States. The results for the two samples were consistent in showing no significant differences in Verbal, Performance, and Full Scale IQs, higher average scores by boys on the Block design and Mazes subtests of spatial ability, and higher average scores by girls on Coding. There was also greater variability in boys than in girls.

The effects of an inquiry-based earth science course on the spatial thinking of pre-service elementary teacher education students

NASA Astrophysics Data System (ADS)

Weakley, Kevin Douglas

This study examined the effectiveness of two geography courses at improving student spatial thinking skills. Spatial thinking is an important cognitive skill in the sciences and everyday life. A taxonomy of spatial thinking was constructed by Gersmehl (2008) in geography education which included core modes assessed in this study: comparison, region, transition, analogy, pattern, and association. Two additional modes related to space over time, change and movement, were also assessed. The central research question in this study is: What are the effects of a pre-service teacher education earth science content course (Geography 1900) that is conceptually designed and inquiry-based on the spatial thinking of university students compared to the Geography 1020 course that follows a lecture format with an atlas study component? The six sub-questions to this central question were: (1) What spatial thinking modes are embedded in the Geography 1900 course based on the Gersmehl (2008) classification of modes of spatial thinking? (2) What modes of spatial thinking do pre-service elementary education students exhibit prior to instruction in Geography 1900 and 1020? (3) What changes occur in spatial thinking and spatial skills as a result of enrolling in and completing a conceptually based, inquiry course (Geography 1900) that has embedded clearly identifiable spatial tasks based on Gersmehl's classification? (4) What are the effects of Geography 1900 on the modes of spatial thinking that students apply at the completion of the course? (5) What modes of spatial thinking do students transfer from the classroom to the outdoors as they move about campus? (6) Are there differences in spatial thinking between the Geography 1900 population and the Geography 1020 comparison sample of students that received a different course treatment? The research used a mixed methods approach with both quantitative and qualitative information. Statistically significant changes were observed in the use of spatial constructs and concepts by students in each of the course treatments that were compared. Students were also observed to apply spatial modes outside the classroom that represented the spatial thinking within the new context of the university environment as they observed and described the landscape.

Development of a portable electrical impedance tomography data acquisition system for near-real-time spatial sensing

NASA Astrophysics Data System (ADS)

Huang, Shieh-Kung; Loh, Kenneth J.

2015-04-01

The main goal of this study was to develop and validate the performance of a miniature and portable data acquisition (DAQ) system designed for interrogating carbon nanotube (CNT)-based thin films for real-time spatial structural sensing and damage detection. Previous research demonstrated that the electrical properties of CNT-based thin film strain sensors were linearly correlated with applied strains. When coupled with an electrical impedance tomography (EIT) algorithm, the detection and localization of damage was possible. In short, EIT required that the film or "sensing skin" be interrogated along its boundaries. Electrical current was injected across a pair of boundary electrodes, and voltage was simultaneously recorded along the remaining electrode pairs. This was performed multiple times to obtain a large dataset needed for solving the EIT spatial conductivity mapping inverse problem. However, one of the main limitations of this technique was the large amount of time required for data acquisition. In order to facilitate the adoption of this technology and for field implementation purposes, a miniature DAQ that could interrogate these CNT-based sensing skins at high sampling rates was designed and tested. The prototype DAQ featured a Howland current source that could generate stable and controlled direct current. Measurement of boundary electrode voltages and the switching of the input, output, and measurement channels were achieved using multiplexer units. The DAQ prototype was fabricated on a two-layer printed circuit board, and it was designed for integration with a prototype wireless sensing system, which is the next phase of this research.

15x optical zoom and extreme optical image stabilisation: diffraction limited integral field spectroscopy with the Oxford SWIFT spectrograph

NASA Astrophysics Data System (ADS)

Tecza, Matthias; Thatte, Niranjan; Clarke, Fraser; Lynn, James; Freeman, David; Roberts, Jennifer; Dekany, Richard

2012-09-01

When commissioned in November 2008 at the Palomar 200 inch Hale Telescope, the Oxford SWIFT I and z band integral field spectrograph, fed by the adaptive optics system PALAO, provided a wide (3×) range of spatial resolutions: three plate scales of 235 mas, 160 mas, and 80 mas per spaxel over a contiguous field-of-view of 89×44 pixels. Depending on observing conditions and guide star brightness we can choose a seeing limited scale of 235 mas per spaxel, or 160 mas and 80 mas per spaxel for very bright guide star AO with substantial increase of enclosed energy. Over the last two years PALAO was upgraded to PALM-3000: an extreme, high-order adaptive optics system with two deformable mirrors with more than 3000 actuators, promising diffraction limited performance in SWIFT's wavelength range. In order to take advantage of this increased spatial resolution we upgraded SWIFT with new pre-optics allowing us to spatially Nyquist sample the diffraction limited PALM-3000 point spread function with 16 mas resolution, reducing the spaxel scale by another factor of 5×. We designed, manufactured, integrated and tested the new pre-optics in the first half of 2011 and commissioned it in December 2011. Here we present the opto-mechanical design and assembly of the new scale changing optics, as well as laboratory and on-sky commissioning results. In optimal observing conditions we achieve substantial Strehl ratios, delivering the near diffraction limited spatial resolution in the I and z bands.

An instrument for the simultaneous acquisition of size, shape, and spectral fluorescence data from single aerosol particles

NASA Astrophysics Data System (ADS)

Hirst, Edwin; Kaye, Paul H.; Foot, Virginia E.; Clark, James M.; Withers, Philip B.

2004-12-01

We describe the construction of a bio-aerosol monitor designed to capture and record intrinsic fluorescence spectra from individual aerosol particles carried in a sample airflow and to simultaneously capture data relating to the spatial distribution of elastically scattered light from each particle. The spectral fluorescence data recorded by this PFAS (Particle Fluorescence and Shape) monitor contains information relating to the particle material content and specifically to possible biological fluorophores. The spatial scattering data from PFAS yields information relating to particle size and shape. The combination of these data can provide a means of aiding the discrimination of bio-aerosols from background or interferent aerosol particles which may have similar fluorescence properties but exhibit shapes and/or sizes not normally associated with biological particles. The radiation used both to excite particle fluorescence and generate the necessary spatially scattered light flux is provided by a novel compact UV fiber laser operating at 266nm wavelength. Particles drawn from the ambient environment traverse the laser beam in single file. Intrinsic particle fluorescence in the range 300-570nm is collected via an ellipsoidal concentrator into a concave grating spectrometer, the spectral data being recorded using a 16-anode linear array photomultiplier detector. Simultaneously, the spatial radiation pattern scattered by the particle over 5°-30° scattering angle and 360° of azimuth is recorded using a custom designed 31-pixel radial hybrid photodiode array. Data from up to ~5,000 particles per second may be acquired for analysis, usually performed by artificial neural network classification.

Using Historical Atlas Data to Develop High-Resolution Distribution Models of Freshwater Fishes

PubMed Central

Huang, Jian; Frimpong, Emmanuel A.

2015-01-01

Understanding the spatial pattern of species distributions is fundamental in biogeography, and conservation and resource management applications. Most species distribution models (SDMs) require or prefer species presence and absence data for adequate estimation of model parameters. However, observations with unreliable or unreported species absences dominate and limit the implementation of SDMs. Presence-only models generally yield less accurate predictions of species distribution, and make it difficult to incorporate spatial autocorrelation. The availability of large amounts of historical presence records for freshwater fishes of the United States provides an opportunity for deriving reliable absences from data reported as presence-only, when sampling was predominantly community-based. In this study, we used boosted regression trees (BRT), logistic regression, and MaxEnt models to assess the performance of a historical metacommunity database with inferred absences, for modeling fish distributions, investigating the effect of model choice and data properties thereby. With models of the distribution of 76 native, non-game fish species of varied traits and rarity attributes in four river basins across the United States, we show that model accuracy depends on data quality (e.g., sample size, location precision), species’ rarity, statistical modeling technique, and consideration of spatial autocorrelation. The cross-validation area under the receiver-operating-characteristic curve (AUC) tended to be high in the spatial presence-absence models at the highest level of resolution for species with large geographic ranges and small local populations. Prevalence affected training but not validation AUC. The key habitat predictors identified and the fish-habitat relationships evaluated through partial dependence plots corroborated most previous studies. The community-based SDM framework broadens our capability to model species distributions by innovatively removing the constraint of lack of species absence data, thus providing a robust prediction of distribution for stream fishes in other regions where historical data exist, and for other taxa (e.g., benthic macroinvertebrates, birds) usually observed by community-based sampling designs. PMID:26075902

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

Electromagnetic Design of a Magnetically-Coupled Spatial Power Combiner

NASA Technical Reports Server (NTRS)

Bulcha, B.; Cataldo, G.; Stevenson, T. R.; U-Yen, K.; Moseley, S. H.; Wollack, E. J.

2017-01-01

The design of a two-dimensional beam-combining network employing a parallel-plate superconducting waveguide with a mono-crystalline silicon dielectric is presented. This novel beam-combining network structure employs an array of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multi-mode region defined by the parallel-plate waveguide. These attributes enable the structures use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. When configured with a suitable corporate-feed power-combiner, this fully sampled array can be used to realize a low-sidelobe apodized response without incurring a reduction in coupling efficiency. To control undesired reflections over a wide range of angles in the finite-sized parallel-plate waveguide region, a wideband meta-material electromagnetic absorber structure is implemented. This adiabatic structure absorbs greater than 99 of the power over the 1.7:1 operational band at angles ranging from normal (0 degree) to near parallel (180 degree) incidence. Design, simulations, and application of the device will be presented.

Big Data Geo-Analytical Tool Development for Spatial Analysis Uncertainty Visualization and Quantification Needs

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J. R.; Baker, D. V.

2015-12-01

As big data computing capabilities are increasingly paired with spatial analytical tools and approaches, there is a need to ensure uncertainty associated with the datasets used in these analyses is adequately incorporated and portrayed in results. Often the products of spatial analyses, big data and otherwise, are developed using discontinuous, sparse, and often point-driven data to represent continuous phenomena. Results from these analyses are generally presented without clear explanations of the uncertainty associated with the interpolated values. The Variable Grid Method (VGM) offers users with a flexible approach designed for application to a variety of analyses where users there is a need to study, evaluate, and analyze spatial trends and patterns while maintaining connection to and communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analysis through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom 'Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation via custom multi-step Hadoop applications, performance benchmarking comparisons, and Hadoop-centric opportunities for greater parallelization of geospatial operations. The presentation includes examples of the approach being applied to a range of subsurface, geospatial studies (e.g. induced seismicity risk).

S4EI (Spectral Sampling with Slicer for Stellar and Extragalactical Instrumentation), a new-generation of 3D spectro-imager dedicated to night astronomy

NASA Astrophysics Data System (ADS)

Sayède, Frédéric; Puech, Mathieu; Mein, Pierre; Bonifacio, Piercarlo; Malherbe, Jean-Marie; Galicher, Raphaël.; Amans, Jean-Philippe; Fasola, Gilles

2014-07-01

Multichannel Subtractive Double Pass (MSDP) spectrographs have been widely used in solar spectroscopy because of their ability to provide an excellent compromise between field of view and spatial and spectral resolutions. Compared with other types of spectrographs, MSDP can deliver simultaneous monochromatic images at higher spatial and spectral resolutions without any time-scanning requirement (as with Fabry-Perot spectrographs), and with limited loss of flux. These performances are obtained thanks to a double pass through the dispersive element. Recent advances with VPH (Volume phase holographic) Grisms as well as with image slicers now make MSDP potentially sensitive to much smaller fluxes. We present S4EI (Spectral Sampling with Slicer for Stellar and Extragalactical Instrumentation), which is a new concept for extending MSDP to night-time astronomy. It is based on new generation reflecting plane image slicers working with large apertures specific to night-time telescopes. The resulting design could be potentially very attractive and innovative for different domains of astronomy, e.g., the simultaneous spatial mapping of accurately flux-calibrated emission lines between OH sky lines in extragalactic astronomy or the simultaneous imaging of stars, exoplanets and interstellar medium. We present different possible MSDP/S4EI configurations for these science cases and expected performances on telescopes such as the VLT.

Minimizing Experimental Setup Time and Effort at APS beamline 1-ID through Instrumentation Design

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

Benda, Erika; Almer, Jonathan; Kenesei, Peter

2016-01-01

Sector 1-ID at the APS accommodates a number of dif-ferent experimental techniques in the same spatial enve-lope of the E-hutch end station. These include high-energy small and wide angle X-ray scattering (SAXS and WAXS), high-energy diffraction microscopy (HEDM, both near and far field modes) and high-energy X-ray tomography. These techniques are frequently combined to allow the users to obtain multimodal data, often attaining 1 μm spatial resolution and <0.05º angular resolution. Furthermore, these techniques are utilized while the sam-ple is thermo-mechanically loaded to mimic real operat-ing conditions. The instrumentation required for each of these techniques and environments has been designedmore » and configured in a modular way with a focus on stability and repeatability between changeovers. This approach allows the end station to be more versatile, capable of collecting multi-modal data in-situ while reducing time and effort typically required for set up and alignment, resulting in more efficient beam time use. Key instrumentation de-sign features and layout of the end station are presented.« less

Comparison between epiphyte assemblages of leaves and rhizomes of the seagrass Posidonia oceanica subjected to different levels of anthropogenic eutrophication

NASA Astrophysics Data System (ADS)

Balata, David; Bertocci, Iacopo; Piazzi, Luigi; Nesti, Ugo

2008-09-01

This paper aimed to compare epiphyte assemblages of leaves and rhizomes of Posidonia oceanica exposed to different levels of concentration of nutrients. The same design including a potentially impacted meadow and two reference meadows was used in each of two locations, characterized by the presence of a city or of suspended cages of a fish farm, respectively. This allowed to test for the consistency of responses of epiphytic assemblages to different sources of eutrophication. In both studies, results documented differences in patterns of composition and abundance of epiphytic assemblages on leaves between disturbed and reference meadows, while assemblages on rhizomes did not appear sensitive to this kind of disturbance. Moreover, in potentially impacted meadows, both assemblages showed different patterns of spatial variability compared to reference assemblages. Species composition and abundance of epiphyte assemblages seemed suitable for detecting moderate nutrient increases, even if adequate sampling designs are needed to separate patterns related to the large natural spatial variability of these systems from those related to changes in environmental conditions.

High-Definition Infrared Spectroscopic Imaging

PubMed Central

Reddy, Rohith K.; Walsh, Michael J.; Schulmerich, Matthew V.; Carney, P. Scott; Bhargava, Rohit

2013-01-01

The quality of images from an infrared (IR) microscope has traditionally been limited by considerations of throughput and signal-to-noise ratio (SNR). An understanding of the achievable quality as a function of instrument parameters, from first principals is needed for improved instrument design. Here, we first present a model for light propagation through an IR spectroscopic imaging system based on scalar wave theory. The model analytically describes the propagation of light along the entire beam path from the source to the detector. The effect of various optical elements and the sample in the microscope is understood in terms of the accessible spatial frequencies by using a Fourier optics approach and simulations are conducted to gain insights into spectroscopic image formation. The optimal pixel size at the sample plane is calculated and shown much smaller than that in current mid-IR microscopy systems. A commercial imaging system is modified, and experimental data are presented to demonstrate the validity of the developed model. Building on this validated theoretical foundation, an optimal sampling configuration is set up. Acquired data were of high spatial quality but, as expected, of poorer SNR. Signal processing approaches were implemented to improve the spectral SNR. The resulting data demonstrated the ability to perform high-definition IR imaging in the laboratory by using minimally-modified commercial instruments. PMID:23317676

High-definition infrared spectroscopic imaging.

PubMed

Reddy, Rohith K; Walsh, Michael J; Schulmerich, Matthew V; Carney, P Scott; Bhargava, Rohit

2013-01-01

The quality of images from an infrared (IR) microscope has traditionally been limited by considerations of throughput and signal-to-noise ratio (SNR). An understanding of the achievable quality as a function of instrument parameters, from first principals is needed for improved instrument design. Here, we first present a model for light propagation through an IR spectroscopic imaging system based on scalar wave theory. The model analytically describes the propagation of light along the entire beam path from the source to the detector. The effect of various optical elements and the sample in the microscope is understood in terms of the accessible spatial frequencies by using a Fourier optics approach and simulations are conducted to gain insights into spectroscopic image formation. The optimal pixel size at the sample plane is calculated and shown much smaller than that in current mid-IR microscopy systems. A commercial imaging system is modified, and experimental data are presented to demonstrate the validity of the developed model. Building on this validated theoretical foundation, an optimal sampling configuration is set up. Acquired data were of high spatial quality but, as expected, of poorer SNR. Signal processing approaches were implemented to improve the spectral SNR. The resulting data demonstrated the ability to perform high-definition IR imaging in the laboratory by using minimally-modified commercial instruments.

Multi-scale occupancy estimation and modelling using multiple detection methods

USGS Publications Warehouse

Nichols, James D.; Bailey, Larissa L.; O'Connell, Allan F.; Talancy, Neil W.; Grant, Evan H. Campbell; Gilbert, Andrew T.; Annand, Elizabeth M.; Husband, Thomas P.; Hines, James E.

2008-01-01

Occupancy estimation and modelling based on detection–nondetection data provide an effective way of exploring change in a species’ distribution across time and space in cases where the species is not always detected with certainty. Today, many monitoring programmes target multiple species, or life stages within a species, requiring the use of multiple detection methods. When multiple methods or devices are used at the same sample sites, animals can be detected by more than one method.We develop occupancy models for multiple detection methods that permit simultaneous use of data from all methods for inference about method-specific detection probabilities. Moreover, the approach permits estimation of occupancy at two spatial scales: the larger scale corresponds to species’ use of a sample unit, whereas the smaller scale corresponds to presence of the species at the local sample station or site.We apply the models to data collected on two different vertebrate species: striped skunks Mephitis mephitis and red salamanders Pseudotriton ruber. For striped skunks, large-scale occupancy estimates were consistent between two sampling seasons. Small-scale occupancy probabilities were slightly lower in the late winter/spring when skunks tend to conserve energy, and movements are limited to males in search of females for breeding. There was strong evidence of method-specific detection probabilities for skunks. As anticipated, large- and small-scale occupancy areas completely overlapped for red salamanders. The analyses provided weak evidence of method-specific detection probabilities for this species.Synthesis and applications. Increasingly, many studies are utilizing multiple detection methods at sampling locations. The modelling approach presented here makes efficient use of detections from multiple methods to estimate occupancy probabilities at two spatial scales and to compare detection probabilities associated with different detection methods. The models can be viewed as another variation of Pollock's robust design and may be applicable to a wide variety of scenarios where species occur in an area but are not always near the sampled locations. The estimation approach is likely to be especially useful in multispecies conservation programmes by providing efficient estimates using multiple detection devices and by providing device-specific detection probability estimates for use in survey design.

MicrOmega IR: a new infrared hyperspectral imaging microscope or in situ analysis

NASA Astrophysics Data System (ADS)

Vaitua, Leroi; Bibring, Jean-Pierre; Berthé, Michel

2017-11-01

MicrOmega IR is an ultra miniaturized Near Infrared hyperspectral microscope for in situ analysis of samples. It is designed to be implemented on board space planetary vehicles (lander and/or rovers). It acquires images of samples typically some 5 mm in width with a spatial sampling of 20 μm. On each pixel, MicrOmega acquires the spectrum in the spectral range 0.9 - 2.6 μm, with a possibility to extend the sensibility up to 4 μm. The spectrum will be measured in up to 300 contiguous spectral channels (600 in the extended range): given the diagnostic spectral features present in this domain, it provides the composition of each spatially resolved constituent. MicrOmega has thus the potential to identify: minerals, such as pyroxene and olivine, ferric oxides, hydrated phases such as phyllosilicates, sulfates and carbonates, ices and organics. The composition of the various phases within a given sample is a critical record of its formation and evolution. Coupled to the mapping information, it provides unique clues to describe the history of the parent body. In particular, the capability to identify hydrated grains and to characterize their adjacent phases has a huge potential in the search for potential bio-relics in Martian samples. This purely non destructive characterization enables further analyses (e.g. through mass spectrometry) to be performed, and/or to contribute to sample selection to return to Earth. MicrOmega IR is coupled to a visible microscope: MicrOmega VIS. Thus, the MicrOmega instrument is developed by an international consortium: IAS (Orsay, France), LESIA (Meudon, France), CBM (Orléans, France), University Of Bern (Bern, Switzerland), IKI (Moscow, Russia). This instrument (MicrOmega IR, MicrOmega VIS and the electronics) is selected for the ESA Exomars mission (launch scheduled for 2013). MicrOmega IR will be used in a reduced spectral range (0.9 - 2.6 μm), due to power, mass and thermal constraints: however, most minerals and other constituents have diagnostic spectral signature in this range. A full demonstrator model of ExoMars/MicrOmega IR has been assembled at IAS and we will present the design and the experimental results.

The space-math link in preschool boys and girls: Importance of mental transformation, targeting accuracy, and spatial anxiety.

PubMed

Wong, Wang I

2017-06-01

Spatial abilities are pertinent to mathematical competence, but evidence of the space-math link has largely been confined to older samples and intrinsic spatial abilities (e.g., mental transformation). The roles of gender and affective factors are also unclear. This study examined the correlations between counting ability, mental transformation, and targeting accuracy in 182 Hong Kong preschoolers, and whether these relationships were weaker at higher spatial anxiety levels. Both spatial abilities related with counting similarly for boys and girls. Targeting accuracy also mediated the male advantage in counting. Interestingly, spatial anxiety moderated the space-math links, but differently for boys and girls. For boys, spatial abilities were irrelevant to counting at high anxiety levels; for girls, the role of anxiety on the space-math link is less clear. Results extend the evidence base of the space-math link to include an extrinsic spatial ability (targeting accuracy) and have implications for intervention programmes. Statement of contribution What is already known on this subject? Much evidence of a space-math link in adolescent and adult samples and for intrinsic spatial abilities. What does this study add? Extended the space-math link to include both intrinsic and extrinsic spatial abilities in a preschool sample. Showed how spatial anxiety moderated the space-math link differently for boys and girls. © 2016 The British Psychological Society.

Big assumptions for small samples in crop insurance

Treesearch

Ashley Elaine Hungerford; Barry Goodwin

2014-01-01

The purpose of this paper is to investigate the effects of crop insurance premiums being determined by small samples of yields that are spatially correlated. If spatial autocorrelation and small sample size are not properly accounted for in premium ratings, the premium rates may inaccurately reflect the risk of a loss.

Spatial capture-recapture

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Sollmann, Rahel; Gardner, Beth

2013-01-01

Spatial Capture-Recapture provides a revolutionary extension of traditional capture-recapture methods for studying animal populations using data from live trapping, camera trapping, DNA sampling, acoustic sampling, and related field methods. This book is a conceptual and methodological synthesis of spatial capture-recapture modeling. As a comprehensive how-to manual, this reference contains detailed examples of a wide range of relevant spatial capture-recapture models for inference about population size and spatial and temporal variation in demographic parameters. Practicing field biologists studying animal populations will find this book to be a useful resource, as will graduate students and professionals in ecology, conservation biology, and fisheries and wildlife management.

Design and Construction of an Optical Computed Tomography Scanner for Polymer Gel Dosimetry Application

PubMed Central

Zakariaee, Seyed Salman; Mesbahi, Asghar; Keshtkar, Ahmad; Azimirad, Vahid

2014-01-01

Polymer gel dosimeter is the only accurate three dimensional (3D) dosimeter that can measure the absorbed dose distribution in a perfect 3D setting. Gel dosimetry by using optical computed tomography (OCT) has been promoted by several researches. In the current study, we designed and constructed a prototype OCT system for gel dosimetry. First, the electrical system for optical scanning of the gel container using a Helium-Neon laser and a photocell was designed and constructed. Then, the mechanical part for two rotational and translational motions was designed and step motors were assembled to it. The data coming from photocell was grabbed by the home-built interface and sent to a personal computer. Data processing was carried out using MATLAB software. To calibrate the system and tune up the functionality of it, different objects was designed and scanned. Furthermore, the spatial and contrast resolution of the system was determined. The system was able to scan the gel dosimeter container with a diameter up to 11 cm inside the water phantom. The standard deviation of the pixels within water flask image was considered as the criteria for image uniformity. The uniformity of the system was about ±0.05%. The spatial resolution of the system was approximately 1 mm and contrast resolution was about 0.2%. Our primary results showed that this system is able to obtain two-dimensional, cross-sectional images from polymer gel samples. PMID:24761377

Fluorescence imaging spectrometer optical design

NASA Astrophysics Data System (ADS)

Taiti, A.; Coppo, P.; Battistelli, E.

2015-09-01

The optical design of the FLuORescence Imaging Spectrometer (FLORIS) studied for the Fluorescence Explorer (FLEX) mission is discussed. FLEX is a candidate for the ESA's 8th Earth Explorer opportunity mission. FLORIS is a pushbroom hyperspectral imager foreseen to be embarked on board of a medium size satellite, flying in tandem with Sentinel-3 in a Sun synchronous orbit at a height of about 815 km. FLORIS will observe the vegetation fluorescence and reflectance within a spectral range between 500 and 780 nm. Multi-frames acquisitions on matrix detectors during the satellite movement will allow the production of 2D Earth scene images in two different spectral channels, called HR and LR with spectral resolution of 0.3 and 2 nm respectively. A common fore optics is foreseen to enhance by design the spatial co-registration between the two spectral channels, which have the same ground spatial sampling (300 m) and swath (150 km). An overlapped spectral range between the two channels is also introduced to simplify the spectral coregistration. A compact opto-mechanical solution with all spherical and plane optical elements is proposed, and the most significant design rationales are described. The instrument optical architecture foresees a dual Babinet scrambler, a dioptric telescope and two grating spectrometers (HR and LR), each consisting of a modified Offner configuration. The developed design is robust, stable vs temperature, easy to align, showing very high optical quality along the whole field of view. The system gives also excellent correction for transverse chromatic aberration and distortions (keystone and smile).

Are two systemic fish assemblage sampling programmes on the upper Mississippi River telling us the same thing?

USGS Publications Warehouse

Dukerschein, J.T.; Bartels, A.D.; Ickes, B.S.; Pearson, M.S.

2013-01-01

We applied an Index of Biotic Integrity (IBI) used on Wisconsin/Minnesota waters of the upper Mississippi River (UMR) to compare data from two systemic sampling programmes. Ability to use data from multiple sampling programmes could extend spatial and temporal coverage of river assessment and monitoring efforts. We normalized for effort and tested fish community data collected by the Environmental Monitoring and Assessment Program-Great Rivers Ecosystems (EMAP-GRE) 2004–2006 and the Long Term Resource Monitoring Program (LTRMP) 1993–2006. Each programme used daytime electrofishing along main channel borders but with some methodological and design differences. EMAP-GRE, designed for baseline and, eventually, compliance monitoring, used a probabilistic, continuous design. LTRMP, designed primarily for baseline and trend monitoring, used a stratified random design in five discrete study reaches. Analysis of similarity indicated no significant difference between EMAP-GRE and LTRMP IBI scores (n=238; Global R= 0.052; significance level=0.972). Both datasets distinguished clear differences only between 'Fair' and 'Poor' condition categories, potentially supporting a 'pass–fail' assessment strategy. Thirteen years of LTRMP data demonstrated stable IBI scores through time in four of five reaches sampled. LTRMP and EMAPGRE IBI scores correlated along the UMR's upstream to downstream gradient (df [3, 25]; F=1.61; p=0.22). A decline in IBI scores from upstream to downstream was consistent with UMR fish community studies and a previous, empirically modelled human disturbance gradient. Comparability between EMAP-GRE (best upstream to downstream coverage) and LTRMP data (best coverage over time and across the floodplain) supports a next step of developing and testing a systemic, multi-metric fish index on the UMR that both approaches could inform.

Spatial scale-dependent habitat heterogeneity influences submarine canyon macrofaunal abundance and diversity off the Main and Northwest Hawaiian Islands

NASA Astrophysics Data System (ADS)

De Leo, Fabio C.; Vetter, Eric W.; Smith, Craig R.; Rowden, Ashley A.; McGranaghan, Matthew

2014-06-01

The mapping of biodiversity on continental margins on landscape scales is highly relevant to marine spatial planning and conservation. Submarine canyons are widespread topographic features on continental and island margins that enhance benthic biomass across a range of oceanic provinces and productivity regimes. However, it remains unclear whether canyons enhance faunal biodiversity on landscape scales relevant to marine protected area (MPA) design. Furthermore, it is not known which physical attributes and heterogeneity metrics can provide good surrogates for large-scale mapping of canyon benthic biodiversity. To test mechanistic hypotheses evaluating the role of different canyon-landscape attributes in enhancing benthic biodiversity at different spatial scales we conducted 34 submersible dives in six submarine canyons and nearby slopes in the Hawaiian archipelago, sampling infaunal macrobenthos in a depth-stratified sampling design. We employed multivariate multiple regression models to evaluate sediment and topographic heterogeneity, canyon transverse profiles, and overall water mass variability as potential drivers of macrobenthic community structure and species richness. We find that variables related to habitat heterogeneity at medium (0.13 km2) and large (15-33 km2) spatial scales such as slope, backscatter reflectivity and canyon transverse profiles are often good predictors of macrobenthic biodiversity, explaining 16-30% of the variance. Particulate organic carbon (POC) flux and distance from shore are also important variables, implicating food supply as a major predictor of canyon biodiversity. Canyons off the high Main Hawaiian Islands (Oahu and Moloka'i) are significantly affected by organic enrichment, showing enhanced infaunal macrobenthos abundance, whereas this effect is imperceptible around the low Northwest Hawaiian Islands (Nihoa and Maro Reef). Variable canyon alpha-diversity and high rates of species turnover (beta-diversity), particularly for polychaetes, suggest that canyons play important roles in maintaining high levels of regional biodiversity in the extremely oligotrophic system of the North Pacific Subtropical Gyre. This information is of key importance to the process of MPA design, suggesting that canyon habitats be explicitly included in marine spatial planning. The low-islands of Nihoa and Maro Reef in the NWHI showed a lack of sustained input of terrestrial and macrolagae detritus, likely having an influence on the observed low macrofaunal abundances (see further discussion of ‘canyon effects’ in Section 4.3), and showing the fundamental role of coastal landscape characteristics in determining the amount and nature of allochthonous organic matter entering the system. Total and highly-mobile invertebrate megafauna abundances were two to three times higher in the submarine canyons and slopes of the MHI contrasted with the NWHI (Vetter et al., 2010), also demonstrating the role of this larger contribution of terrestrial and coastal organic enrichment in the MHI contrasted with the NWHI.

GHGSat-D: Greenhouse gas plume imaging and quantification from space using a Fabry-Perot imaging spectrometer

NASA Astrophysics Data System (ADS)

McKeever, J.; Durak, B. O. A.; Gains, D.; Jervis, D.; Varon, D. J.; Germain, S.; Sloan, J. J.

2017-12-01

GHGSat, Inc. has launched the first satellite designed to detect and quantify greenhouse gas emissions from individual industrial sites. Our demonstration satellite GHGSat-D or "CLAIRE" was launched in June 2016. It weighs less than 15 kg and its primary instrument is a miniaturized Fabry-Perot imaging spectrometer with spectral resolution on the order of 0.1 nm. The spectral bandpass is 1635-1670 nm, giving the instrument access to absorption bands of both CO2 and CH4. Our system is based on targeted observations rather than global coverage, and our spatial imaging resolution is a key differentiator. Specifically, with a ground sampling distance of <50 m within a 12 km field of view, we are able to spatially resolve the increased column densities associated with individual emission plumes. For a given emission rate and wind speed the magnitude of the local excess column increases approximately linearly as pixel resolution decreases. Consequently, at GHGSat's resolution the total column can exceed local background by well over 10% for many industrial sites with strong but realistic emission rates. GHGSat uses a novel measurement and retrievals concept where the emitter site of interest is captured in a sequence of 150-200 overlapping two-dimensional images. The combined effect of the Fabry-Perot resonator and the scrolling scene gives a different spectral sampling of each surface location in every image. While our data processing toolchain does not produce a conventional hyperspectral dataset, it does yield a spectral decomposition of the spatially resolved signal that is compared to a model that includes atmospheric radiative transfer and the instrument's pixel-dependent spectral responsivity. Our presentation will describe the instrument design, concept of operations and retrievals approach. We will also present images and results from GHGSat-D at different processing levels, including high-resolution column density retrievals. An observation of the degassing flux of methane from the outlet of a recently impounded hydroelectric reservoir will be shown as an example. Finally we discuss some performance limitations of GHGSat-D and our plans to overcome them as we update the instrument design for the next satellites.

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

OpenMSI Arrayed Analysis Tools v2.0

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

BOWEN, BENJAMIN; RUEBEL, OLIVER; DE ROND, TRISTAN

2017-02-07

Mass spectrometry imaging (MSI) enables high-resolution spatial mapping of biomolecules in samples and is a valuable tool for the analysis of tissues from plants and animals, microbial interactions, high-throughput screening, drug metabolism, and a host of other applications. This is accomplished by desorbing molecules from the surface on spatially defined locations, using a laser or ion beam. These ions are analyzed by a mass spectrometry and collected into a MSI 'image', a dataset containing unique mass spectra from the sampled spatial locations. MSI is used in a diverse and increasing number of biological applications. The OpenMSI Arrayed Analysis Tool (OMAAT)more » is a new software method that addresses the challenges of analyzing spatially defined samples in large MSI datasets, by providing support for automatic sample position optimization and ion selection.« less

Monitoring air quality in mountains: Designing an effective network

USGS Publications Warehouse

Peterson, D.L.

2000-01-01

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring

NASA Technical Reports Server (NTRS)

Frolik, Jeff; Skalka, Christian

2012-01-01

This invention is designed to ascertain the snow water equivalence (SWE) of snowpacks with better spatial and temporal resolutions than present techniques. The approach is ground-based, as opposed to some techniques that are air-based. In addition, the approach is compact, non-destructive, and can be communicated with remotely, and thus can be deployed in areas not possible with current methods. Presently there are two principal ground-based techniques for obtaining SWE measurements. The first is manual snow core measurements of the snowpack. This approach is labor-intensive, destructive, and has poor temporal resolution. The second approach is to deploy a large (e.g., 3x3 m) snowpillow, which requires significant infrastructure, is potentially hazardous [uses a approximately equal to 200-gallon (approximately equal to 760-L) antifreeze-filled bladder], and requires deployment in a large, flat area. High deployment costs necessitate few installations, thus yielding poor spatial resolution of data. Both approaches have limited usefulness in complex and/or avalanche-prone terrains. This approach is compact, non-destructive to the snowpack, provides high temporal resolution data, and due to potential low cost, can be deployed with high spatial resolution. The invention consists of three primary components: a robust wireless network and computing platform designed for harsh climates, new SWE sensing strategies, and algorithms for smart sampling, data logging, and SWE computation.

Occupants' Perceptions of Amenity and Efficiency for Verification of Spatial Design Adequacy.

PubMed

Lee, Sangwon; Wohn, Kwangyun

2016-01-14

The best spatial design condition to satisfy the occupancy needs of amenity and efficiency is determined through analyzing the spatial design adequacy (SDA). In this study, the relationship between the space design elements and space on future occupants' perception are analyzed. The thirty-three participants reported their self-evaluated SDA that describes the quality of eight alternative housing living rooms with different spatial factors. The occupants were guided through the perception processing elaboration in order for them to evaluate the actual perception in the real space. The findings demonstrated that the spatial size (e.g., width, depth, and height) is significantly correlated with the overall satisfaction of amenity. It is also found that the spatial shape (e.g., the width-to-depth ratio, the height-to-area ratio, and room shape) may significantly influence the overall satisfaction of efficiency. The findings also demonstrate that the causal relationship between the spatial factors and space is clearly present in the occupants' perception, reflecting the time-sequential characteristics of the actual experience divided into amenity and efficiency. This result indicates that the correlation between the spatial factors and space of SDA under the occupants' perception processing elaboration can be a useful guide to predict the occupancy satisfaction of amenity and efficiency in real spaces.

Occupants’ Perceptions of Amenity and Efficiency for Verification of Spatial Design Adequacy

PubMed Central

Lee, Sangwon; Wohn, Kwangyun

2016-01-01

The best spatial design condition to satisfy the occupancy needs of amenity and efficiency is determined through analyzing the spatial design adequacy (SDA). In this study, the relationship between the space design elements and space on future occupants’ perception are analyzed. The thirty-three participants reported their self-evaluated SDA that describes the quality of eight alternative housing living rooms with different spatial factors. The occupants were guided through the perception processing elaboration in order for them to evaluate the actual perception in the real space. The findings demonstrated that the spatial size (e.g., width, depth, and height) is significantly correlated with the overall satisfaction of amenity. It is also found that the spatial shape (e.g., the width-to-depth ratio, the height-to-area ratio, and room shape) may significantly influence the overall satisfaction of efficiency. The findings also demonstrate that the causal relationship between the spatial factors and space is clearly present in the occupants’ perception, reflecting the time-sequential characteristics of the actual experience divided into amenity and efficiency. This result indicates that the correlation between the spatial factors and space of SDA under the occupants’ perception processing elaboration can be a useful guide to predict the occupancy satisfaction of amenity and efficiency in real spaces. PMID:26784211

Relationship of Pupils' Spatial Perception and Ability with Their Performance in Geography

ERIC Educational Resources Information Center

Likouri, Anna-Aikaterini; Klonari, Aikaterini; Flouris, George

2017-01-01

The aim of this study was to investigate the correlation between pupils' spatial perception and abilities and their performance in geography. The sample was 600 6th-grade pupils from various areas of Greece selected by the cluster sampling method. The study results showed that: a) the vast majority of pupils showed low spatial ability; b) there…

The Bayesian group lasso for confounded spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin E.; Walsh, Daniel P.

2017-01-01

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

Long-term airborne contamination studied by attic dust in an industrial area: Ajka, Hungary

NASA Astrophysics Data System (ADS)

Völgyesi, P.; Jordan, G.; Szabo, Cs.

2012-04-01

Heavy industrial activities such as mining, metal industry, coal fired power plants have produced large amount of by-products and wide-spread pollution, particularly in the period of centrally dictated economy after WWII, in Hungary. Several studies suggest that significant amount of these pollutants have been deposited in the urban environment. Nowadays, more than half of the world's population is living in urban areas and people spend almost 80% of their lives indoors in developed countries increasing human health risk due to contamination present in urban dwellings. Attic dust sampling was applied to determine the long-term airborne contamination load in the industrial town of Ajka (Hungary). There has been a high industrial activity in Ajka since the end of the 19th century. In addition to aluminum and alumina industry, coal mining, coal fired power plant and glass industry sites, generated numerous waste heaps which act as multi-contamination sources in the area. In October 2010 the Ajka red mud tailings pond failed and caused an accidental regional contamination of international significance. The major objective of this research was to study and map the spatial distribution of heavy metal contamination in airborne attic dust samples. At 27 sampling sites 30 attic dust samples were collected. Sampling strategy followed a grid-based stratified random sampling design. In each cell a house for attic dust sample collection was selected that was located the closest to a randomly generated point in the grid cell. The project area covers a 8x8 grid of 1x1 km cells with a total area of 64 km2. In order to represent long-term industrial pollution, houses with attics kept intact for at least 30-40 years were selected for sampling. Sampling included the collection of background samples remotely placed from the industrialized urban area. The concentration of the major and toxic elements (Al, Ca, Fe, K, Mg, Mn, Na, P, S, and As, Ba, Cd, Co, Cr, Cu, Li, Mo, Ni, Pb, Se, Sn, Sr, Ti, V, Zn) were measured with ICP-OES and the mercury content was measured with atom absorption spectrometry. Our results show a good spatial correlation of contamination sources and attic dust sampling locations reveal spatial trends as well. Attic dust seems to be an efficient and cheep sampling medium to study long-term airborne contamination and possibly associated human health risk in an industrial area.

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

Report on Component 2 - Designing New Methods for Visualizing Text in Spatial Contexts

DTIC Science & Technology

2012-10-31

W9132V-11-P-0010 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Alexander Savelyev , Scott Pezanowski, Anthony C. Robinson, and Alan M...e Component 2 – Designing New Methods for Visualizing Text in Spatial Contexts Alexander Savelyev , Scott Pezanowski, Anthony Robinson and Alan...Center, Penn State University Report on Component 2: Component 2 – Designing New Methods for Visualizing Text in Spatial Contexts Alexander

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

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

PubMed

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

2016-01-07

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

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

A twin study of spatial and non-spatial delayed response performance in middle age.

PubMed

Kremen, William S; Mai, Tuan; Panizzon, Matthew S; Franz, Carol E; Blankfeld, Howard M; Xian, Hong; Eisen, Seth A; Tsuang, Ming T; Lyons, Michael J

2011-06-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic influences). Non-spatial alternation (NSA), which may involve greater reliance on processing of subgoals, was significantly more difficult than spatial alternation (SA). Despite their similarities, NSA and SA scores were uncorrelated. NSA performance was worse when administered second; there was no SA order effect. NSA scores were modestly heritable (h(2)=.25; 26); SA was not. There was shared genetic variance between NSA scores and general intellectual ability (r(g)=.55; .67), but this also suggests genetic influences specific to NSA. Compared with findings from small, selected control samples, high "failure" rates in this community-based sample raise concerns about interpretation of brain dysfunction in elderly or patient samples. Copyright © 2011 Elsevier Inc. All rights reserved.

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

PubMed

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

2013-12-01

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

A Twin Study of Spatial and Non-Spatial Delayed Response Performance in Middle Age

PubMed Central

Kremen, William S.; Mai, Tuan; Panizzon, Matthew S.; Franz, Carol E.; Blankfeld, Howard M.; Xian, Hong; Eisen, Seth A.; Tsuang, Ming T.; Lyons, Michael J.

2011-01-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic influences). Non-spatial alternation (NSA), which may involve greater reliance on processing of subgoals, was significantly more difficult than spatial alternation (SA). Despite their similarities, NSA and SA scores were uncorrelated. NSA performance was worse when administered second; there was no SA order effect. NSA scores were modestly heritable (h2=.25; 26); SA was not. There was shared genetic variance between NSA scores and general intellectual ability (rg=.55; .67), but this also suggests genetic influences specific to NSA. Compared with findings from small, selected control samples, high “failure” rates in this community-based sample raise concerns about interpretation of brain dysfunction in elderly or patient samples. PMID:21477911

The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations

NASA Astrophysics Data System (ADS)

Wake, David A.; Bundy, Kevin; Diamond-Stanic, Aleksandar M.; Yan, Renbin; Blanton, Michael R.; Bershady, Matthew A.; Sánchez-Gallego, José R.; Drory, Niv; Jones, Amy; Kauffmann, Guinevere; Law, David R.; Li, Cheng; MacDonald, Nicholas; Masters, Karen; Thomas, Daniel; Tinker, Jeremy; Weijmans, Anne-Marie; Brownstein, Joel R.

2017-09-01

We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing signal-to-noise ratio, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on I-band absolute magnitude (M I ), or, for a small subset of our sample, M I and color (NUV - I). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to M I and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (R e ), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color-magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range 5× {10}8≤slant {M}* ≤slant 3× {10}11 {M}⊙ {h}-2 and are sampled at median physical resolutions of 1.37 and 2.5 kpc for the Primary and Secondary samples, respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume-limited sample.

Distributed encoding of spatial and object categories in primate hippocampal microcircuits

PubMed Central

Opris, Ioan; Santos, Lucas M.; Gerhardt, Greg A.; Song, Dong; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.

2015-01-01

The primate hippocampus plays critical roles in the encoding, representation, categorization and retrieval of cognitive information. Such cognitive abilities may use the transformational input-output properties of hippocampal laminar microcircuitry to generate spatial representations and to categorize features of objects, images, and their numeric characteristics. Four nonhuman primates were trained in a delayed-match-to-sample (DMS) task while multi-neuron activity was simultaneously recorded from the CA1 and CA3 hippocampal cell fields. The results show differential encoding of spatial location and categorization of images presented as relevant stimuli in the task. Individual hippocampal cells encoded visual stimuli only on specific types of trials in which retention of either, the Sample image, or the spatial position of the Sample image indicated at the beginning of the trial, was required. Consistent with such encoding, it was shown that patterned microstimulation applied during Sample image presentation facilitated selection of either Sample image spatial locations or types of images, during the Match phase of the task. These findings support the existence of specific codes for spatial and numeric object representations in primate hippocampus which can be applied on differentially signaled trials. Moreover, the transformational properties of hippocampal microcircuitry, together with the patterned microstimulation are supporting the practical importance of this approach for cognitive enhancement and rehabilitation, needed for memory neuroprosthetics. PMID:26500473

Characterizing exposures to airborne metals and nanoparticle emissions in a refinery.

PubMed

Miller, Arthur; Drake, Pamela L; Hintz, Patrick; Habjan, Matt

2010-07-01

An air quality survey was conducted at a precious metals refinery in order to evaluate worker exposures to airborne metals and to provide detailed characterization of the aerosols. Two areas within the refinery were characterized: a furnace room and an electro-refining area. In line with standard survey practices, both personal and area air filter samples were collected on 37-mm filters and analyzed for metals by inductively coupled plasma-atomic emission spectroscopy. In addition to the standard sampling, measurements were conducted using other tools, designed to provide enhanced characterization of the workplace aerosols. The number concentration and number-weighted particle size distribution of airborne particles were measured with a fast mobility particle sizer (FMPS). Custom-designed software was used to correlate particle concentration data with spatial location data to generate contour maps of particle number concentrations in the work areas. Short-term samples were collected in areas of localized high concentrations and analyzed using transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS) to determine particle morphology and elemental chemistry. Analysis of filter samples indicated that all of the workers were exposed to levels of silver above the Occupational Safety and Health Administration permissible exposure limit of 0.01 mg m(-3) even though the localized ventilation was functioning. Measurements with the FMPS indicated that particle number concentrations near the furnace increased up to 1000-fold above the baseline during the pouring of molten metal. Spatial mapping revealed localized elevated particle concentrations near the furnaces and plumes of particles rising into the stairwells and traveling to the upper work areas. Results of TEM/EDS analyses confirmed the high number of nanoparticles measured by the FMPS and indicated the aerosols were rich in metals including silver, lead, antimony, selenium, and zinc. Results of the survey were used to deduce appropriate strategies for mitigation of worker exposure to airborne metals.

Wildlife monitoring across multiple spatial scales using grid-based sampling

Treesearch

Kevin S. McKelvey; Samuel A. Cushman; Michael K. Schwartz; Leonard F. Ruggiero

2009-01-01

Recently, noninvasive genetic sampling has become the most effective way to reliably sample occurrence of many species. In addition, genetic data provide a rich data source enabling the monitoring of population status. The combination of genetically based animal data collected at known spatial coordinates with vegetation, topography, and other available covariates...

Impact of Satellite Viewing-Swath Width on Global and Regional Aerosol Optical Thickness Statistics and Trends

NASA Technical Reports Server (NTRS)

Colarco, P. R.; Kahn, R. A.; Remer, L. A.; Levy, R. C.

2014-01-01

We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Alongtrack and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (approximately 400-800 km) and single pixel width (approximately 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal-regional mean AOT. These AOT spatial sampling artifacts comprise up to 60%of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10 deg) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5 deg) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal-regional spatial sampling artifact in AOT Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-ofatmosphere aerosol radiative forcing of 2-3 W m(sup-2). These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

Cryogenic STM in 3D vector magnetic fields realized through a rotatable insert.

PubMed

Trainer, C; Yim, C M; McLaren, M; Wahl, P

2017-09-01

Spin-polarized scanning tunneling microscopy (SP-STM) performed in vector magnetic fields promises atomic scale imaging of magnetic structure, providing complete information on the local spin texture of a sample in three dimensions. Here, we have designed and constructed a turntable system for a low temperature STM which in combination with a 2D vector magnet provides magnetic fields of up to 5 T in any direction relative to the tip-sample geometry. This enables STM imaging and spectroscopy to be performed at the same atomic-scale location and field-of-view on the sample, and most importantly, without experiencing any change on the tip apex before and after field switching. Combined with a ferromagnetic tip, this enables us to study the magnetization of complex magnetic orders in all three spatial directions.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Spatial resolution properties of motion-compensated tomographic image reconstruction methods.

PubMed

Chun, Se Young; Fessler, Jeffrey A

2012-07-01

Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.

Assessment of long-term gas sampling design at two commercial manure-belt layer barns.

PubMed

Chai, Li-Long; Ni, Ji-Qin; Chen, Yan; Diehl, Claude A; Heber, Albert J; Lim, Teng T

2010-06-01

Understanding temporal and spatial variations of aerial pollutant concentrations is important for designing air quality monitoring systems. In long-term and continuous air quality monitoring in large livestock and poultry barns, these systems usually use location-shared analyzers and sensors and can only sample air at limited number of locations. To assess the validity of the gas sampling design at a commercial layer farm, a new methodology was developed to map pollutant gas concentrations using portable sensors under steady-state or quasi-steady-state barn conditions. Three assessment tests were conducted from December 2008 to February 2009 in two manure-belt layer barns. Each barn was 140.2 m long and 19.5 m wide and had 250,000 birds. Each test included four measurements of ammonia and carbon dioxide concentrations at 20 locations that covered all operating fans, including six of the fans used in the long-term sampling that represented three zones along the lengths of the barns, to generate data for complete-barn monitoring. To simulate the long-term monitoring, gas concentrations from the six long-term sampling locations were extracted from the 20 assessment locations. Statistical analyses were performed to test the variances (F-test) and sample means (t test) between the 6- and 20-sample data. The study clearly demonstrated ammonia and carbon dioxide concentration gradients that were characterized by increasing concentrations from the west to east ends of the barns following the under-cage manure-belt travel direction. Mean concentrations increased from 7.1 to 47.7 parts per million (ppm) for ammonia and from 2303 to 3454 ppm for carbon dioxide from the west to east of the barns. Variations of mean gas concentrations were much less apparent between the south and north sides of the barns, because they were 21.2 and 20.9 ppm for ammonia and 2979 and 2951 ppm for carbon dioxide, respectively. The null hypotheses that the variances and means between the 6- and 20-sample data were equal at alpha = 0.05 (P > 0.05) were accepted for both gases. The results proved that the long-term gas sampling design was valid in this instance and suggested that the gas sampling design in these two barns was one of the best on the basis of available long-term monitoring instrumentation at reasonable cost.