Local-scale Parameters Research Articles

Can agri-environmental schemes enhance non-target species? Effects of sown wildflower fields on the common hamster (Cricetus cricetus) at local and landscape scales

During the last decades, agriculture has been rapidly intensified, resulting in a strong decline in species diversity. Therefore the common agricultural policy (CAP) of the EU implemented agri-environmental schemes (AES) for an environmentally-friendly management of agricultural areas. Sown wildflower fields are one of these measures aimed at enhancing insect diversity and related ecosystem services. However, little is known about the impacts of AES on rare and non-target species. To study the effect of these AES on a non-target species, the occurrence of the endangered common hamster (Cricetus cricetus) was mapped by counting reopened winter burrows on paired sown wildflower fields and agricultural fields in North-West Bavaria, Germany. Concentration effects in sown wildflower fields and the distribution of C. cricetus in adjacent agricultural fields were studied by mapping burrows up to a distance of 200m from sown wildflower and agricultural fields. Furthermore, C. cricetus occurrence in relation to local (vegetation density, cover of grasses, vegetation height, size of wildflower fields) and landscape scale parameters (percentage of arable land, grassland, fallow land, distance to the nearest forest, and settlement) of sown wildflower fields was analysed. Results show that there was a concentration of C. cricetus in sown wildflower fields, while densities in adjacent agricultural fields were constantly low. Hamster occurrence was negatively related to vegetation density and grass cover on sown wildflower fields and positively related to distance to the nearest forests, percentage of arable land and fallow land around wildflower fields. In conclusion, we could show that sown wildflower fields can be an ideal habitat for non-target species, such as the common hamster. However, local and landscape scale parameters of sown wildflower fields need to be considered when designing AES.

Research on Segmentation of Vertebral Bodies from Spinal MR Images based on Gauss Weighted and Local Contraction

This paper present a segmentation of vertebral bodies from spinal MR images based on neighborhood informa- tion Gauss weighted and local contraction. First use a cut-off window (5�5) around each pixel and stack the gray values inside the window into a vector, adopt the Gaussian kernel function to incorporate local spatial information, an adaptive local scaling parameter is used to refine the segmentation rather than a fixed scaling parameter to avoid the manually tuned parameter. Finally, the built affinity is introduced into the segmentation process by using a graph-based method to achieve the complete target. Extensively experiments show that the present method can segment the vertebral bodies smoothly and clearly, and it has stronger anti-noise property and higher segmentation precision than the conventional methods. The robust and accurate result of segmentation should serve image registration and the analysis of spinal de- formities. It is a general method for segmenting object that can develop to segment other tissues and organs.

Optical properties of 1D and 2D approximants of quasi-crystalline structures

The possibility of identifying 1D and 2D approximants of quasi-crystalline structures, based on recording local patterns and scaling parameters in probe-beam fields, is considered. The effect of structural defects on the shape of pattern formations is estimated.

Phonetic segmentation of speech signal using local singularity analysis

This paper presents the application of a radically novel approach, called the Microcanonical Multiscale Formalism (MMF) to speech analysis. MMF is based on precise estimation of local scaling parameters that describe the inter-scale correlations at each point in the signal domain and provides efficient means for studying local non-linear dynamics of complex signals. In this paper we introduce an efficient way for estimation of these parameters and then, we show that they convey relevant information about local dynamics of the speech signal that can be used for the task of phonetic segmentation. We thus develop a two-stage segmentation algorithm: for the first step, we introduce a new dynamic programming technique to efficiently generate an initial list of phoneme-boundary candidates and in the second step, we use hypothesis testing to refine the initial list of candidates. We present extensive experiments on the full TIMIT database. The results show that our algorithm is significantly more accurate than state-of-the-art ones.

Adaptive Segmentation of Vertebral Bodies from Sagittal MR Images Based on Local Spatial Information and Gaussian Weighted Chi-Square Distance

We present a novel method for the automatic segmentation of the vertebral bodies from 2D sagittal magnetic resonance (MR) images of the spine. First, a new affinity matrix is constructed by incorporating neighboring information, which local intensity is considered to depict the image and overcome the noise effectively. Second, the Gaussian kernel function is to weight chi-square distance based on the neighboring information, which the vital spatial structure of the image is introduced to improve the accuracy of the segmentation task. Third, an adaptive local scaling parameter is utilized to facilitate the image segmentation and avoid the optimal configuration of controlling parameter manually. The encouraging results on the spinal MR images demonstrate the advantage of the proposed method over other methods in terms of both efficiency and robustness.

Physicochemical Heterogeneity Controls on Uranium Bioreduction Rates at the Field Scale

It has been demonstrated in laboratory systems that U(VI) can be reduced to immobile U(IV) by bacteria in natural environments. The ultimate efficacy of bioreduction at the field scale, however, is often challenging to quantify and depends on site characteristics. In this work, uranium bioreduction rates at the field scale are quantified, for the first time, using an integrated approach. The approach combines field data, inverse and forward hydrological and reactive transport modeling, and quantification of reduction rates at different spatial scales. The approach is used to explore the impact of local scale (tens of centimeters) parameters and processes on field scale (tens of meters) system responses to biostimulation treatments and the controls of physicochemical heterogeneity on bioreduction rates. Using the biostimulation experiments at the Department of Energy Old Rifle site, our results show that the spatial distribution of hydraulic conductivity and solid phase mineral (Fe(III)) play a critical role in determining the field-scale bioreduction rates. Due to the dependence on Fe-reducing bacteria, field-scale U(VI) bioreduction rates were found to be largely controlled by the abundance of Fe(III) minerals at the vicinity of the injection wells and by the presence of preferential flow paths connecting injection wells to down gradient Fe(III) abundant areas.

Development and application of a reactive plume-in-grid model: evaluation over Greater Paris

Abstract. Emissions from major point sources are badly represented by classical Eulerian models. An overestimation of the horizontal plume dilution, a bad representation of the vertical diffusion as well as an incorrect estimate of the chemical reaction rates are the main limitations of such models in the vicinity of major point sources. The plume-in-grid method is a multiscale modeling technique that couples a local-scale Gaussian puff model with an Eulerian model in order to better represent these emissions. We present the plume-in-grid model developed in the air quality modeling system Polyphemus, with full gaseous chemistry. The model is evaluated on the metropolitan Île-de-France region, during six months (summer 2001). The subgrid-scale treatment is used for 89 major point sources, a selection based on the emission rates of NOx and SO2. Results with and without the subgrid treatment of point emissions are compared, and their performance by comparison to the observations on measurement stations is assessed. A sensitivity study is also carried out, on several local-scale parameters as well as on the vertical diffusion within the urban area. Primary pollutants are shown to be the most impacted by the plume-in-grid treatment. SO2 is the most impacted pollutant, since the point sources account for an important part of the total SO2 emissions, whereas NOx emissions are mostly due to traffic. The spatial impact of the subgrid treatment is localized in the vicinity of the sources, especially for reactive species (NOx and O3). Ozone is mostly sensitive to the time step between two puff emissions which influences the in-plume chemical reactions, whereas the almost-passive species SO2 is more sensitive to the injection time, which determines the duration of the subgrid-scale treatment. Future developments include an extension to handle aerosol chemistry, and an application to the modeling of line sources in order to use the subgrid treatment with road emissions. The latter is expected to lead to more striking results, due to the importance of traffic emissions for the pollutants of interest.

Local Similarity in the Stable Boundary Layer and Mixing-Length Approaches: Consistency of Concepts

In stably stratified flows vertical movement of eddies is limited by the fact that kinetic energy is converted into potential energy, leading to a buoyancy displacement scale z B . Our new mixing-length concept for turbulent transport in the stable boundary layer follows a rigid-wall analogy, in the sense that we assume that the buoyancy length scale is similar to neutral length scaling. This implies that the buoyancy length scale is: ? B = ? B z B , with ? B ? ?, the von Karman constant. With this concept it is shown that the physical relevance of the local scaling parameter z/? naturally appears, and that the ? coefficient of the log-linear similarity functions is equal to c/? 2, where c is a constant close to unity. The predicted value ? ? 1/? 2 = 6.25 lies within the range found in observational studies. Finally, it is shown that the traditionally used inverse linear interpolation between the mixing length in the neutral and buoyancy limits is inconsistent with the classical log-linear stability functions. As an alternative, a log-linear consistent interpolation method is proposed.

Identifying key environmental variables structuring benthic fauna for establishing a biotic typology for Greek running waters

A central aspect of the Water Framework Directive 2000/60/EC addressed to Member Countries is to proceed to type-specific ecological assessment and classification by establishing typology systems. Sixty-four permanent stream sites distributed throughout mainland Greece and islands were assessed with macroinvertebrate indicators to evaluate their ecological quality. Local and catchment scale parameters were determined and recorded to obtain an integrated assessment of the main factors affecting stream integrity and macroinvertebrate communities. Twenty-three sites were classified as reference or good status in terms of biological, chemical and hydromorphological quality with the use of various metrics. Multivariate statistical techniques were performed (MDS, BIOENV, correlation analysis and PCA) to investigate the main environmental factors structuring benthic macroinvertebrate communities and to select candidate environmental variables for establishing a biotic typology for Hellenic rivers. The results revealed relatively distinct macroinvertebrate communities within defined abiotic zones of the country. Assemblages of macroinvertebrate fauna were most strongly associated to differences in geographical position, altitude, slope, catchment area, current velocity, conductivity and water temperature. In view of the lack of sufficient data at the country level on the three last variables and after considering cause–effect relationships between large scale variables and the latter, it has been demonstrated that a number of catchment scale variables could be used as robust surrogates.

Imprints from the global cosmological expansion to the local spacetime dynamics

We study the general relativistic spacetime metrics surrounding massive cosmological objects, such as suns, stars, galaxies or galaxy clusters. The question addressed here is the transition of local, object-related spacetime metrics into the global, cosmological Robertson-Walker metrics. We demonstrate that the answer often quoted for this problem from the literature, the so-called Einstein-Straus vacuole, which connects a static outer Schwarzschild solution with the time-dependent Robertson-Walker universe, is inadequate to describe the local spacetime of a gravitationally bound system. Thus, we derive here an alternative model describing such bound systems by a metrics more closely tied to the fundamental problem of structure formation in the early universe and obtain a multitude of solutions characterising the time-dependence of a local scale parameter. As we can show, a specific solution out of this multitude is able to, as a by-product, surprisingly enough, explain the presently much discussed phenomenon of the PIONEER anomaly.

Modeling Envelope Statistics of Blood and Myocardium for Segmentation of Echocardiographic Images

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 × 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (σ 2/μ) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images. (E-mail: m.m.nillesen@cukz.umcn.nl)

Revisiting the Cape Cod Bacteria Injection Experiment Using a Stochastic Modeling Approach

Bromide and resting-cell bacteria tracer tests conducted in a sandy aquifer at the U.S. Geological Survey Cape Cod site in 1987 were reinterpreted using a three-dimensional stochastic approach. Bacteria transport was coupled to colloid filtration theory through functional dependence of local-scale colloid transport parameters upon hydraulic conductivity and seepage velocity in a stochastic advection-dispersion/attachment-detachment model. Geostatistical information on the hydraulic conductivity (K) field that was unavailable at the time of the original test was utilized as input. Using geostatistical parameters, a groundwater flow and particle-tracking model of conservative solute transport was calibrated to the bromide-tracer breakthrough data. An optimization routine was employed over 100 realizations to adjust the mean and variance of the natural-logarithm of hydraulic conductivity (InK) field to achieve best fit of a simulated, average bromide breakthrough curve. A stochastic particle-tracking model for the bacteria was run without adjustments to the local-scale colloid transport parameters. Good predictions of mean bacteria breakthrough were achieved using several approaches for modeling components of the system. Simulations incorporating the recent Tufenkji and Elimelech (Environ. Sci. Technol. 2004, 38, 529-536) correlation equation for estimating single collector efficiency were compared to those using the older Rajagopalan and Tien (AIChEJ. 1976, 22, 523-533) model. Both appeared to work equally well at predicting mean bacteria breakthrough using a constant mean bacteria diameter for this set of field conditions. Simulations using a distribution of bacterial cell diameters available from original field notes yielded a slight improvement in the model and data agreement compared to simulations using an average bacterial diameter. The stochastic approach based on estimates of local-scale parameters for the bacteria-transport process reasonably captured the mean bacteria transport behavior and calculated an envelope of uncertainty that bracketed the observations in most simulation cases.

The conformal alpha shape filtration

Conformal alpha shapes are a new filtration of the Delaunay triangulation of a finite set of points in ℝd. In contrast to (ordinary) alpha shapes the new filtration is parameterized by a local scale parameter instead of the global scale parameter in alpha shapes. The local scale parameter conforms to the local geometry and is motivated from applications and previous algorithms in surface reconstruction. We show how conformal alpha shapes can be used for surface reconstruction of non-uniformly sampled surfaces, which is not possible with alpha shapes.

A parameter scaling concept for estimating field-scale hydraulic functions of layered soils

Predicting flow and transport in unsaturated porous media is often hampered by limited data and the uncertainties in constitutive property information at the appropriate spatial scales. Some studies have used inverse flow modeling for parameter estimation to overcome these limitations. However, determination of the soil hydraulic parameters of layered soils remains a challenge since inverting for too many parameters can lead to the nonuniqueness of parameter values. Here we propose a parameter scaling method that reduces the number of parameters to be estimated. First, parameter scaling factors are determined using local-scale parameter values. After assigning scaling factors to the corresponding soil textures in the field, the reference hydraulic parameter values at the field scale can be estimated through inverse modeling of well-designed field experiments. Finally, parameters for individual textures are obtained through inverse scaling of the reference values. The number of unknown variables is reduced by a factor equal to the number of textures (M) and the simulation time is reduced by the square of the number of textures (M 2). The proposed method was tested using two infiltration-drainage experiments in layered soils. The STOMP numerical simulator was combined with the inverse modeling program, UCODE, to estimate the hydraulic parameters. Simulation errors were significantly reduced after applying parameter scaling and inverse modeling. When compared to the use of local-scale parameters, parameter scaling reduced the sum of squared weighted residual by 93-96%.

Recognizing goldfish? or Local scale selection for recognition techniques

This paper addresses the problem of the local scale parameter selection for recognition techniques based on Gaussian derivatives. Patterns are represented in a local subspace or feature space of which each dimension is a scale normalized receptive field (a unit composed of normalized Gaussian-based filters). Scale invariance is obtained by automatic selection of an appropriate local scale [Lindeberg, Int. J. Comput. Vision 30 (2) (1998) 79] and followed by normalization of the receptive field to the appropriate scale. The power of a scale equivariant feature space is shown by experimental results for point correspondences in images of different scales and the recognition of objects under scale variations. The approach is validated with the results of experiments in the discrimination of three goldfish species. During the training phase, each goldfish is isolated from the others and its behavior is uncontrolled. Data are structurally represented in a feature space for the recognition of static deformable object configurations. A statistical description is used for object recognition based on temporal activity. Recognition is processed using the static configuration of fish and their temporal activity.

Detecting and Identifying Mirror-Symmetric Letters in the Periphery: A Test of the Equivalent-Size Hypothesis

If the visual mechanisms underlying form perception scale similarly with eccentricity, then performance in regions of different eccentricity should be characterised by a single function of the form f( s/ e) where s is a spatial variable, like size or spatial frequency, and e is a parameter that represents the local scale at that eccentricity. This formulation implies that performance at a given size s0 and eccentricity should be identical to that at a size s1= s0 e1/ e0, at a different eccentricity, where e0 and e1 are the local scale parameters for the two eccentricities. We refer to this as the equivalent-size hypothesis. We tested the equivalent-size hypothesis by measuring contrast thresholds for detection and identification of four mirror symmetric letters (b, p, d, q) for a series of sizes at each of three eccentricities (2, 4, and 8 deg). Psychometric functions were obtained for each size and eccentricity with the use of a spatial, 4-alternative forced-choice, double-judgment technique. First, observers specified at which of four positions around the fovea the stimulus appeared. Then they responded with the letter name. At each eccentricity, contrast thresholds for detection and identification as a function of size were described well by a power function. A single power function scaled for eccentricity was able to account for either the detection or the identification behaviour, and a single scaling parameter for the two tasks would not suffice.

Anion Transport in a Piedmont Ultisol: II. Local-Scale Parameters

Field-scale transport parameters obtained from tile drain data in two large conventionally tilled plots were reported in the first paper in this series. Our objectives in this paper were to determine the relationship between local-scale transport parameters and macropore distributions measured with columns in one of these plots and to compare local-scale transport parameters with the field-scale parameters. Forty undisturbed soil columns (15 cm in diameter, 33-64 cm in length) were taken from Plot 1 described in the first paper. Transport parameters were determined from a Br breakthrough curve (BTC) with CXTFIT. Macropore distributions were determined from computed tomography (CT) scanning and by sectioning the columns after adding methylene blue dye. Local-scale saturated hydraulic conductivity (K s ), pore water velocity (V), and dispersivity (λ) were highly variable (coefficient of variation of 77, 74, and 41%, respectively) and lognormally distributed. The K s was positively correlated with the number of 5- to 10-mm-diameter CT scan macropores at a depth of 35 to 40 cm near the top of the Bt horizon. Dye patterns indicated that preferential flow began at about this depth. This may be the zone where flow becomes restricted and highly dependent on macropores. Mean local-scale λ (6.6 cm) was similar to the estimated field-scale values (3.4 and 5.3 cm) for the unsaturated zone to a depth of 20 cm. This implied that variation among local-scale V in the field experiment was much less than that observed in the columns, probably because the surface was not ponded in the field. A deterministic approach with mean values of local-scale parameters adequately described the estimated field-scale BTC.

Convective-Dispersive Stream Tube Model for Field-Scale Solute Transport: II. Examples and Calibration

The use of the stream tube model developed in the first part of this study is illustrated for several examples with a stochastic pore-water velocity, v, and distribution coefficient, Kd. The model allows quantification of the concentration variance in the horizontal plane to evaluate models for transport in heterogeneous fields. Increased vertical solute spreading due to stochastic local-scale parameters is accompanied by increased horizontal variations of the field-scale mean concentration. Solute application at the surface is modeled as a boundary value problem (BVP) and an initial value problem (IVP). The field-averaged concentration vs. depth exhibits more spreading for the BVP than the IVP since a variable solute mass is applied to each stream tube in the latter case. Flow is also modeled by a lognormal probability density function for the saturated conductivity, Ks, and the unit gradient assumption instead of v. The use of a random v instead of Ks is preferable for small variations in water content. Results of the stream tube model are compared with those of a one-dimensional macroscopic convection-dispersion equation (CDE) with effective parameters (i.e., depth-dependent constants). When these constants are determined from time moments of the field-scale flux-averaged concentration, ĉf, for the BVP, the stream tube model and the macroscopic CDE will give different results if the effective parameters are used to model other transport scenarios. Finally, the stream tube model was fitted to the concentrations obtained from a detailed numerical simulation of flow and transport in a (hypothetical) heterogeneous field. The (simple) stream tube model appears to provide a sensible description of the field-averaged concentration and variance.

Direct computation of shape cues using scale-adapted spatial derivative operators

This paper addresses the problem of computing cues to the three-dimensional structure of surfaces in the world directly from the local structure of the brightness pattern of either a single monocular image or a binocular image pair. It is shown that starting from Gaussian derivatives of order up to two at a range of scales in scale-space, local estimates of (i) surface orientation from monocular texture foreshortening, (ii) surface orientation from monocular texture gradients, and (iii) surface orientation from the binocular disparity gradient can be computed without iteration or search, and by using essentially the same basic mechanism. The methodology is based on a multi-scale descriptor of image structure called the windowed second moment matrix, which is computed with adaptive selection of both scale levels and spatial positions. Notably, this descriptor comprises two scale parameters; a local scale parameter describing the amount of smoothing used in derivative computations, and an integration scale parameter determining over how large a region in space the statistics of regional descriptors is accumulated. Experimental results for both synthetic and natural images are presented, and the relation with models of biological vision is briefly discussed.

Theory of the local scale parameter method for EDM

The determination of a representative refractive index for the wave path is the main limitation of the attainable accuracy in electronic distance measurement. To overcome this limitation the length ratio method was initially proposed and later developed into the local scale parameter (LSP) method. In this paper, the mathematical model of the LSP method is derived for electro-optical distance measurement from first principles based on the physics of the atmospheric boundary layer. The model does not rely on ‘standard atmospheres’. It is shown that atmospheric temperatures and pressures must be observed at instrument stations but not at reflector stations. Appropriate LSP field procedures and the results of some field experiments are summarized. The method consistently produces accuracies of better than ±1 ppm. Use of the method is recommended for high precision (trilateration) networks, which need to be measured repeatedly and where absolute scale is not relevant.