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Journal articles on the topic 'Spatial field'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 January 2023

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1

Kovaříček, P., and J. Hůla. "Field capacity determination from GPS spatial data." Research in Agricultural Engineering 49, No. 3 (February 8, 2012): 75–79. http://dx.doi.org/10.17221/4955-rae.

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For agricultural machinery management the actually reached machines capacity has a considerable importance. The data recorded by GPS monitoring enable to correct machines work productivity under concrete operational conditions. Assessment of machine aggregates operation records has proved effect of the operational factors onto operational efficiency reached on particular plots. The theoretical efficiency given by exploitation characteristics of machines has decreased effect of higher share of non-productive travels within small and irregular plots almost by 25%. In this paper we are dealing with searching for correlation between field speed and travelled unit path and defined classes of size, length and plot shape. The resulting knowledge of field efficiency on plots properties will enable to make more accurate the machines planned operation.

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2

Munandar, Aris, Enok Maryani, Dede Rohmat, and Mamat Ruhimat. "Assessment on Geography Field study at Universities in Indonesia." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 19, no. 1 (October 3, 2019): 1–10. http://dx.doi.org/10.21009/spatial.191.01.

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In Geography Study Program, fieldstudy is the hallmark of geography outdoor learning. The similar activities of fieldstudy are fieldwork, fieldtrip, outing, excursion, cooks tours and others. The implementation of fieldstudy in the universities of teacher training has the similarity in its naming, its definition, its purpose, material of the study, the duration of the activity, the location of the fieldstudy, and data processing. The difference of the fieldstudy implementation lies on the ratio of supervisor to students, funding, outcome product and assessment. Universities that conduct the fieldstudy should review the curriculum in its implementation so that the credit, the assessed product and process have the similarity both in the credit and the supervisors who assess.

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3

As'ari, Ruli, and Erni Mulyanie. "The Use of Local Landscape as a Field Laboratory for Geography of Education." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 19, no. 2 (December 31, 2019): 1–7. http://dx.doi.org/10.21009/spatial.192.1.

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Geographical skills that need to be shared by each geographer in general are map skills, field skills, and satellite image interpretation skills. To achieve field skills competency, a location is needed to be used as material for practicum studies for each subject. The Geography Education Field Laboratory can be studied in depth based on an analysis of the level of learning needs. The basis of the lab location requirements as a laboratory is seen from the laboratory function as an area to carry out careful and accurate testing and measurement of the phenomenon under study. The study was carried out through the identification of local landscapes by delineating the area through the utilization of satellite citera, and identifying potential from each area that was chosen descriptively. In this study, the Gunung Galunggung area can be used as a Physical Field Laboratory for Geography and Kampung Naga Education can be used as a Field Laboratory for Social and Cultural Geography.

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4

Koch, Erwan. "Spatial Risk Measures and Rate of Spatial Diversification." Risks 7, no. 2 (May 2, 2019): 52. http://dx.doi.org/10.3390/risks7020052.

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An accurate assessment of the risk of extreme environmental events is of great importance for populations, authorities and the banking/insurance/reinsurance industry. Koch (2017) introduced a notion of spatial risk measure and a corresponding set of axioms which are well suited to analyze the risk due to events having a spatial extent, precisely such as environmental phenomena. The axiom of asymptotic spatial homogeneity is of particular interest since it allows one to quantify the rate of spatial diversification when the region under consideration becomes large. In this paper, we first investigate the general concepts of spatial risk measures and corresponding axioms further and thoroughly explain the usefulness of this theory for both actuarial science and practice. Second, in the case of a general cost field, we give sufficient conditions such that spatial risk measures associated with expectation, variance, value-at-risk as well as expected shortfall and induced by this cost field satisfy the axioms of asymptotic spatial homogeneity of order 0, −2, −1 and −1, respectively. Last but not least, in the case where the cost field is a function of a max-stable random field, we provide conditions on both the function and the max-stable field ensuring the latter properties. Max-stable random fields are relevant when assessing the risk of extreme events since they appear as a natural extension of multivariate extreme-value theory to the level of random fields. Overall, this paper improves our understanding of spatial risk measures as well as of their properties with respect to the space variable and generalizes many results obtained in Koch (2017).

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5

Johnson, D. L. "SPATIAL AUTOCORRELATION, SPATIAL MODELING, AND IMPROVEMENTS IN GRASSHOPPER SURVEY METHODOLOGY." Canadian Entomologist 121, no. 7 (July 1989): 579–88. http://dx.doi.org/10.4039/ent121579-7.

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AbstractAnalysis of 10 years of grasshopper survey data (1978–1987) indicated that grasshopper populations in fields can be reliably predicted from roadside survey counts. Direct estimation of grasshopper densities in crop fields is no longer required for summaries of infestation levels or forecasts. Spatial autocorrelation was significant and positive for both roadside and field counts. The coefficient of variation of the field counts was greater than that of the roadside counts in each of the last 10 years. Population density was summarized by crop type and sampling method for the last 10 years. Linear regressions fitted to the 1978–1984 grasshopper survey data were used to estimate field population density from crop type and roadside counts in 1985–1987. Maps of population density were generated from the predicted and observed field counts with SPANS, a microcomputer-based geographic information system. Large coefficients of association (73–79%) between the predicted and observed maps attested to the sufficiency of road-side counts as the basis for production of population density maps.

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6

Si, Bing Cheng, and R. Gary Kachanoski. "Field-scale N fertilizer recommendations: The spatial covariance problem." Canadian Journal of Soil Science 82, no. 1 (February 1, 2002): 59–64. http://dx.doi.org/10.4141/s01-040.

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Theory is needed to estimate field-scale crop response and calibration relationships (soil test versus recommended fertilize r rate) from local scale measurements, in fields with spatially variable soil properties. The objective of this study is to present a theoretical stochastic framework for examining the influence of the spatial variability of soil properties, and covariance between soil properties, on field-scale crop response to fertilizer. An analytical solution of the general stochastic scaling equation is given for the specific case of wheat grain yield response to applied N fertilizer with variable soil-N test and available water in Saskatchewan, Canada. The analytical solution indicates spatial variance of soil properties within fields influences field average yield response to applied fertilizer. The field-scale maximum economic rate of fertilizer N (MERN), depends not only on the average soil properties, but also on (1) the amount of variability of soil properties in the field, and (2) the correlation between the spatial patterns of soil properties (e.g., soil test and available water). For the specific soil examined, positive spatial correlation between soil-N test and available water significantly increases MERN, for the same average soil test and available water. Negative correlation decreases MERN. Key Words: Fertilizer recommendation, soil test, spatial variability, crop response, soil water

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7

Borůvka, L., H. Donátová, and K. Němeček. "Spatial distribution and correlation of soil properties in a field: a case study." Plant, Soil and Environment 48, No. 10 (December 22, 2011): 425–32. http://dx.doi.org/10.17221/4391-pse.

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Analysis of spatial distribution and correlation of soil properties represents an important outset for precision agriculture. This paper presents an analysis of spatial distribution and mutual correlations, both classical and spatial, of soil properties in an agricultural field in Klučov. Clay and fine silt content, pH, organic carbon content (C<sub>org</sub>), moisture (Q), total porosity (Pt), capillary porosity (P<sub>c</sub>), and coefficients of aggregate vulnerability to fast wetting (K<sub>v1</sub>), to slow wetting and drying (K<sub>v2</sub>), and to mechanical impacts (K<sub>v3</sub>) were determined. Semivariogram ranges from 206 m (clay content) to 1120 m (K<sub>v3</sub>) were detected. Many relationships between soil properties were spatially based. Fine silt content and Corg proved to be the most important soil properties controlling all the three aggregate vulnerability coefficients, which was not clear for K<sub>v2</sub> from classical correlation only. Determined spatial correlations and similarities in spatial distribution may serve as groundwork in delineation of different zones for site-specific management.

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8

Gary, S. Peter, and Dan Winske. "Field/field spatial correlation function: Electromagnetic proton cyclotron instability." Journal of Geophysical Research: Space Physics 101, A2 (February 1, 1996): 2661–68. http://dx.doi.org/10.1029/95ja02988.

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9

Watson, Andrew B. "The Field of View, the Field of Resolution, and the Field of Contrast Sensitivity." Journal of Perceptual Imaging 1, no. 1 (January 1, 2018): 10505–1. http://dx.doi.org/10.2352/j.percept.imaging.2018.1.1.010505.

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Abstract The Field of View (FoV), the Field of Resolution, and the Field of Contrast Sensitivity describe three progressively more detailed descriptions of human spatial sensitivity at angles relative to fixation. The FoV is the range of visual angles that can be sensed by an eye. The Field of Resolution describes the highest spatial frequency that can be sensed at each angle. The Field of Contrast Sensitivity describes contrast sensitivity at each spatial frequency, at each visual angle. These three concepts can be unified with the aid of the Pyramid of Visibility, a simplified model of contrast sensitivity as a function of spatial frequency, temporal frequency, and luminance or retinal illuminance. This unified model provides simple yet powerful observations about the Field of Contrast Sensitivity. I have fit this model to a number of published measurements of peripheral contrast sensitivity. This allows us to test the validity of the model, and to estimate its parameters. Although the model is a simplification, I believe it provides an invaluable guide in a range of applications in visual technology.

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10

Donohoe, Aaron, and David S. Battisti. "The Amplitude Asymmetry between Synoptic Cyclones and Anticyclones: Implications for Filtering Methods in Feature Tracking." Monthly Weather Review 137, no. 11 (November 1, 2009): 3874–87. http://dx.doi.org/10.1175/2009mwr2837.1.

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Abstract The “background” state is commonly removed from synoptic fields by use of either a spatial or temporal filter prior to the application of feature tracking. Commonly used spatial and temporal filters applied to sea level pressure data admit substantially different information to be included in the synoptic fields. The spatial filter retains a time-mean field that has comparable magnitude to a typical synoptic perturbation. In contrast, the temporal filter removes the entire time-mean field. The inclusion of the time-mean spatially filtered field biases the feature tracking statistics toward large cyclone (anticyclone) magnitudes in the regions of climatological lows (highs). The resulting cyclone/anticyclone magnitude asymmetries in each region are found to be inconsistent with the unfiltered data fields and merely result from the spurious inclusion of the time-mean fields in the spatially filtered data. The temporally filtered fields do not suffer from the same problem and produce modest cyclone/anticyclone magnitude asymmetries that are consistent with the unfiltered data. This analysis suggests that the weather forecaster’s assertion that cyclones have larger amplitudes than anticyclones is due to a composite of a small magnitude asymmetry in the synoptic waves and a large contribution from inhomogeneity in the background (stationary) field.

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11

Slater, P. B. "A Field Theory of Spatial Interaction." Environment and Planning A: Economy and Space 21, no. 1 (January 1989): 121–26. http://dx.doi.org/10.1068/a210121.

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Spatial interaction—the flows of people, goods, or other entities from place to place—can be conceptualized as occurring in a scalar field of influences, both of external origin (that is, travel costs) and of internal origin (that is, temporal correlations between flows). Conventional spatial interaction models, however, incorporate into their cost functions only the exogenous effects. This omission is addressed. The presence of significant positive and negative correlations between flows would be indicative of a ‘frustrated’ system of interactions, one in which all tendencies cannot be simultaneously respected. Cost (energy) minimization (a generalization of the classical problem of transportation) that can be pursued by means of simulated annealing, reduces these stresses. Enhancement of the tensions, on the other hand, leads to an equivalence with the quadratic transportation problem of Dorigo and Tobler, and suggests that the eigenvalues of the matrix of correlations between flows, are estimates of travel cost for a set of ‘eigenflows’.

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12

Hristopulos, Dionissios T., and Emilio Porcu. "Multivariate Spartan spatial random field models." Probabilistic Engineering Mechanics 37 (July 2014): 84–92. http://dx.doi.org/10.1016/j.probengmech.2014.06.005.

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13

Alexander, Matthew, and Peter G. Bergmann. "The gravitational field at spatial infinity." Foundations of Physics 16, no. 5 (May 1986): 445–54. http://dx.doi.org/10.1007/bf01882728.

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14

Kachanoski, R. G., and G. L. Fairchild. "Field scale fertilizer recommendations: The spatial scaling problem." Canadian Journal of Soil Science 76, no. 1 (February 1, 1996): 1–6. http://dx.doi.org/10.4141/cjss96-001.

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Soil fertility may vary considerably within a field. The effects of variable soil fertility on the relationships among average crop yield response, average soil test, and fertilizer applied evenly to a field have not been examined. This paper develops stochastic equations to describe the average yield gain on a field basis from the application of a single constant rate of fertilizer, in fields with variable soil fertility. The equations are solved numerically for the specific case of nitrogen fertilizer on corn (Zea mays L.) in Ontario, Canada. The results suggest that since the relationships among yield response, soil test, and applied fertilizer are non-linear, a single soil test calibration cannot exist for fields with different spatial variability. Soil test calibrations obtained from sites with low variability (for example small plots) will not hold for sites with higher variability (for example farm fields). Calibrations obtained from sites with low variability will under-predict the optimum economic fertilizer rate for sites with low variability will under-predict the optimum economic fertilizer rate for sites with high variability. The results do not invalidate soil test calibration relationships per se. The challenge is to combine these calibrations with additional knowledge about the spatial distribution and field-scale variability of soil test values in order to maximize economic benefit. Key words: Spatial variability, soil test, fertilizer recommendation, yield, corn, field scale

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15

Nicolaescu, Dan. "Spatial distribution of the electric field for field emission microtriodes." Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures 14, no. 3 (May 1996): 1930. http://dx.doi.org/10.1116/1.588957.

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16

Meredith, M. A., and B. E. Stein. "Spatial determinants of multisensory integration in cat superior colliculus neurons." Journal of Neurophysiology 75, no. 5 (May 1, 1996): 1843–57. http://dx.doi.org/10.1152/jn.1996.75.5.1843.

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1. Although a representation of multisensory space is contained in the superior colliculus, little is known about the spatial requirements of multisensory stimuli that influence the activity of neurons here. Critical to this problem is an assessment of the registry of the different receptive fields within individual multisensory neurons. The present study was initiated to determine how closely the receptive fields of individual multisensory neurons are aligned, the physiological role of that alignment, and the possible functional consequences of inducing receptive-field misalignment. 2. Individual multisensory neurons in the superior colliculus of anesthetized, paralyzed cats were studied with the use of standard extracellular recording techniques. The receptive fields of multisensory neurons were large, as reported previously, but exhibited a surprisingly high degree of spatial coincidence. The average proportion of receptive-field overlap was 86% for the population of visual-auditory neurons sampled. 3. Because of this high degree of intersensory receptive-field correspondence, combined-modality stimuli that were coincident in space tended to fall within the excitatory regions of the receptive fields involved. The result was a significantly enhanced neuronal response in 88% of the multisensory neurons studied. If stimuli were spatially disparate, so that one fell outside its receptive field, either a decreased response occurred (56%), or no intersensory effect was apparent (44%). 4. The normal alignment of the different receptive fields of a multisensory neuron could be disrupted by passively displacing the eyes, pinnae, or limbs/body. In no case was a shift in location or size observed in a neuron's other receptive field(s) to compensate for this displacement. The physiological result of receptive-field misalignment was predictable and based on the location of the stimuli relative to the new positions of their respective receptive fields. Now, for example, one component of a spatially coincident pair of stimuli might fall outside its receptive field and inhibit the other's effects. 5. These data underscore the dependence of multisensory integrative responses on the relationship of the different stimuli to their corresponding receptive fields rather than to the spatial relationship of the stimuli to one another. Apparently, the alignment of different receptive fields for individual multisensory neurons ensures that responses to combinations of stimuli derived from the same event are integrated to increase the salience of that event. Therefore the maintenance of receptive-field alignment is critical for the appropriate integration of converging sensory signals and, ultimately, elicitation of adaptive behaviors.

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17

Krempaský, Július, and Miroslava Smrčinová. "Chemical temporal and spatial structures in strong magnetic field." Collection of Czechoslovak Chemical Communications 54, no. 5 (1989): 1232–43. http://dx.doi.org/10.1135/cccc19891232.

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Temporal and spatial structures in the Belousov-Zhabotinskii systems in constant electric and strong magnetic fields are studied in this paper. Unlike a random generation of chemical wave center in a system without the influence of an electromagnetic field we have observed that only one wave forms in the presence of electric and magnetic fields of suitable intensity and induction. Its speed of propagation depends on the connected fields. A theory of this phenomenon has been developed and the obtained results are in a good agreement with experimentally measured dependences of the temporal period of chemical waves on electric field intensity and magnetic field induction.

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18

Peters, Gareth W., Ido Nevat, Sai Ganesh Nagarajan, and Tomoko Matsui. "Spatial Warped Gaussian Processes: Estimation and Efficient Field Reconstruction." Entropy 23, no. 10 (October 11, 2021): 1323. http://dx.doi.org/10.3390/e23101323.

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A class of models for non-Gaussian spatial random fields is explored for spatial field reconstruction in environmental and sensor network monitoring. The family of models explored utilises a class of transformation functions known as Tukey g-and-h transformations to create a family of warped spatial Gaussian process models which can support various desirable features such as flexible marginal distributions, which can be skewed, leptokurtic and/or heavy-tailed. The resulting model is widely applicable in a range of spatial field reconstruction applications. To utilise the model in applications in practice, it is important to carefully characterise the statistical properties of the Tukey g-and-h random fields. In this work, we study both the properties of the resulting warped Gaussian processes as well as using the characterising statistical properties of the warped processes to obtain flexible spatial field reconstructions. In this regard we derive five different estimators for various important quantities often considered in spatial field reconstruction problems. These include the multi-point Minimum Mean Squared Error (MMSE) estimators, the multi-point Maximum A-Posteriori (MAP) estimators, an efficient class of multi-point linear estimators based on the Spatial-Best Linear Unbiased (S-BLUE) estimators, and two multi-point threshold exceedance based estimators, namely the Spatial Regional and Level Exceedance estimators. Simulation results and real data examples show the benefits of using the Tukey g-and-h transformation as opposed to standard Gaussian spatial random fields in a real data application for environmental monitoring.

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19

Shulman, Gordon L., and James Wilson. "Spatial Frequency and Selective Attention to Spatial Location." Perception 16, no. 1 (February 1987): 103–11. http://dx.doi.org/10.1068/p160103.

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The effect of spatial attention on the detectability of gratings of different spatial frequency was measured using a probe technique. Three experiments are reported in which the detectability of full-field probe gratings was measured while subjects analyzed stimuli presented in either the central or the peripheral visual field. Selective attention to peripheral stimuli produced a facilitation at low frequencies and a decrement at high frequencies. These effects disappeared under forced-choice presentation.

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20

Takeuchi, Masatoshi, and Teruaki Irie. "Effects of field margins and other uncultivated fields on Orthoptera assemblages in the mountainous paddy field area of northeast Japan." Zoology and Ecology 29, no. 1 (July 13, 2019): 52–64. http://dx.doi.org/10.35513/21658005.2019.1.7.

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To understand how farmlands help maintain biodiversity, we investigated the relationship between habitat heterogeneity and Orthoptera community composition on multiple spatial scales. First, we determined the impact of 12 environmental variables on the Orthoptera community diversity by sampling 37 quadrats in uncultivated fields over a broad spatial scale. Canonical correspondence analysis (CCA) demonstrated that environmental parameters influenced species composition. The first two canonical axes were associated with forest cover, grass (including harvested dried grass in some cases), bare or paddy fields, and plants with tall stems. Secondly, we conducted a local-scale survey of Orthoptera assemblages in an operational farm unit consisting of paddy fields, fallow fields, marginal grass fields, and secondary forests. Eleven Orthoptera species (46%) were found exclusively on specific vegetation types. Thirdly, we carried out a habitat-scale survey to elucidate the correspondence between consecutive spatial changes in vegetation and Orthoptera community composition in a paddy field and surrounding marginal fields. Even within narrower ranges, the compositional habitat heterogeneity induced changes in the dominant Orthoptera species composition. These results indicate that a high degree of habitat segregation occurs among Orthoptera species in field margins and in uncultivated fields, and that farmland management significantly affects spatial distribution of Orthoptera.

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21

Elmore, Kimberly L., Michael E. Baldwin, and David M. Schultz. "Field Significance Revisited: Spatial Bias Errors in Forecasts as Applied to the Eta Model." Monthly Weather Review 134, no. 2 (February 1, 2006): 519–31. http://dx.doi.org/10.1175/mwr3077.1.

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Abstract The spatial structure of bias errors in numerical model output is valuable to both model developers and operational forecasters, especially if the field containing the structure itself has statistical significance in the face of naturally occurring spatial correlation. A semiparametric Monte Carlo method, along with a moving blocks bootstrap method is used to determine the field significance of spatial bias errors within spatially correlated error fields. This process can be completely automated, making it an attractive addition to the verification tools already in use. The process demonstrated here results in statistically significant spatial bias error fields at any arbitrary significance level. To demonstrate the technique, 0000 and 1200 UTC runs of the operational Eta Model and the operational Eta Model using the Kain–Fritsch convective parameterization scheme are examined. The resulting fields for forecast errors for geopotential heights and winds at 850, 700, 500, and 250 hPa over a period of 14 months (26 January 2001–31 March 2002) are examined and compared using the verifying initial analysis. Specific examples are shown, and some plausible causes for the resulting significant bias errors are proposed.

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22

Berrocal, Veronica J., Adrian E. Raftery, and Tilmann Gneiting. "Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts." Monthly Weather Review 135, no. 4 (April 1, 2007): 1386–402. http://dx.doi.org/10.1175/mwr3341.1.

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Abstract Forecast ensembles typically show a spread–skill relationship, but they are also often underdispersive, and therefore uncalibrated. Bayesian model averaging (BMA) is a statistical postprocessing method for forecast ensembles that generates calibrated probabilistic forecast products for weather quantities at individual sites. This paper introduces the spatial BMA technique, which combines BMA and the geostatistical output perturbation (GOP) method, and extends BMA to generate calibrated probabilistic forecasts of whole weather fields simultaneously, rather than just weather events at individual locations. At any site individually, spatial BMA reduces to the original BMA technique. The spatial BMA method provides statistical ensembles of weather field forecasts that take the spatial structure of observed fields into account and honor the flow-dependent information contained in the dynamical ensemble. The members of the spatial BMA ensemble are obtained by dressing the weather field forecasts from the dynamical ensemble with simulated spatially correlated error fields, in proportions that correspond to the BMA weights for the member models in the dynamical ensemble. Statistical ensembles of any size can be generated at minimal computational cost. The spatial BMA technique was applied to 48-h forecasts of surface temperature over the Pacific Northwest in 2004, using the University of Washington mesoscale ensemble. The spatial BMA ensemble generally outperformed the BMA and GOP ensembles and showed much better verification results than the raw ensemble, both at individual sites, for weather field forecasts, and for forecasts of composite quantities, such as average temperature in National Weather Service forecast zones and minimum temperature along the Interstate 90 Mountains to Sound Greenway.

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23

Jacobson, Josh, William Kleiber, Michael Scheuerer, and Joseph Bellier. "Beyond univariate calibration: verifying spatial structure in ensembles of forecast fields." Nonlinear Processes in Geophysics 27, no. 3 (August 31, 2020): 411–27. http://dx.doi.org/10.5194/npg-27-411-2020.

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Abstract. Most available verification metrics for ensemble forecasts focus on univariate quantities. That is, they assess whether the ensemble provides an adequate representation of the forecast uncertainty about the quantity of interest at a particular location and time. For spatially indexed ensemble forecasts, however, it is also important that forecast fields reproduce the spatial structure of the observed field and represent the uncertainty about spatial properties such as the size of the area for which heavy precipitation, high winds, critical fire weather conditions, etc., are expected. In this article we study the properties of the fraction of threshold exceedance (FTE) histogram, a new diagnostic tool designed for spatially indexed ensemble forecast fields. Defined as the fraction of grid points where a prescribed threshold is exceeded, the FTE is calculated for the verification field and separately for each ensemble member. It yields a projection of a – possibly high-dimensional – multivariate quantity onto a univariate quantity that can be studied with standard tools like verification rank histograms. This projection is appealing since it reflects a spatial property that is intuitive and directly relevant in applications, though it is not obvious whether the FTE is sufficiently sensitive to misrepresentation of spatial structure in the ensemble. In a comprehensive simulation study we find that departures from uniformity of the FTE histograms can indeed be related to forecast ensembles with biased spatial variability and that these histograms detect shortcomings in the spatial structure of ensemble forecast fields that are not obvious by eye. For demonstration, FTE histograms are applied in the context of spatially downscaled ensemble precipitation forecast fields from NOAA's Global Ensemble Forecast System.

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Park, No-Wook, and Phaedon C. Kyriakidis. "A Geostatistical Approach to Spatial Quality Assessment of Coarse Spatial Resolution Remote Sensing Products." Journal of Sensors 2019 (June 19, 2019): 1–14. http://dx.doi.org/10.1155/2019/7297593.

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A geostatistical framework for spatial quality assessment framework of coarse resolution remote sensing products is presented that can account for either the scale difference or the uncertainty of reference value prediction at coarse resolutions. A set of multiple reference field realizations is first generated at a fine spatial resolution using geostatistical simulation to explore the uncertainty in the true unknown reference field. The upscaling of multiple reference field realizations to coarse resolution is then followed to match the spatial resolution of the target remote sensing product and create coarse resolution reference fields. The simulated reference values at each coarse pixel are compared to the corresponding reported value from the coarse resolution remote sensing product, yielding alternative error values, from which several location-dependent statistics such as mean error, mean absolute error, and probability of overestimation can be computed. An experiment involving monthly Tropical Rainfall Measuring Mission (TRMM) precipitation products and point-level rain gauge data over South Korea illustrates the applicability of the proposed approach. The spatially distributed error statistics are useful to identify areas with larger errors and the degree of overestimation in the study area, leading to the identification of areas with unreliable estimates within the TRMM precipitation products. Therefore, it is expected that the geostatistical assessment framework presented in this paper can be effectively used to evaluate the spatial quality of coarse resolution remote sensing products.

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25

Brodie, Eric E. "Manual Asymmetry in Weight Discrimination: Hand or Spatial-Field Advantage?" Perception 18, no. 3 (June 1989): 397–402. http://dx.doi.org/10.1068/p180397.

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Sixty subjects who were either left-handed or right-handed performed one-handed weight discrimination using their left and right hands in the left and right spatial fields. Differential thresholds, for the left and right hands of both left-handed and right-handed subjects, were found to be lower in the spatial field contralateral to the ear which proved superior in a dichotic listening test. It is concluded that manual asymmetry for weight discrimination results primarily from the mapping of sensorimotor events in the spatial fields onto contralateral cerebral cortex, with an advantage in the spatial field contralateral to the nonlanguage cerebral hemisphere.

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26

Biswas, A., and B. C. Si. "Spatial relationship between soil hydraulic and soil physical properties in a farm field." Canadian Journal of Soil Science 89, no. 4 (August 1, 2009): 473–88. http://dx.doi.org/10.4141/cjss08052.

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The relationship between soil properties may vary with their spatial separation. Understanding this relationship is important in predicting hydraulic parameters from other soil physical properties. The objective of this study was to identify spatially dependent relationships between hydraulic parameters and soil physical properties. Regularly spaced (3-m) undisturbed soil samples were collected along a 384 m transect from a farm field at Smeaton, Saskatchewan. Saturated hydraulic conductivity, the soil water retention curve, and soil physical properties were measured. The scaling parameter, van Genuchten scaling parameter α (VGα), and curve shape parameter, van Genuchten curve shape parameter n (VGn), were obtained by fitting the van Genuchten model to measured soil moisture retention data. Results showed that the semivariograms of soil properties exhibited two different spatial structures at spatial separations of 20 and 120 m, respectively. A strong spatial structure was observed in organic carbon, saturated hydraulic conductivity (Ks), sand, and silt; whereas a weak structure was found for VGα and VGn. Correlation circle analysis showed strong spatially dependent relationships of Ks and VGα; with soil physical properties, but weak relationships of θs and VGn with soil physical properties. The spatially dependent relationships between soil physical and soil hydraulic parameters should be taken into consideration when developing pedotransfer functions. Key words: Spatial relationship, geostatistics, linear coregionalization model, principal component analysis, pedotransfer function

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27

Cardina, John, Gregg A. Johnson, and Denise H. Sparrow. "The nature and consequence of weed spatial distribution." Weed Science 45, no. 3 (June 1997): 364–73. http://dx.doi.org/10.1017/s0043174500092997.

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Seed dispersal, interacting with environmental disturbance and management across heterogeneous landscapes, results in irregular weed spatial distributions. Describing, predicting, and managing weed populations requires an understanding of how weeds are distributed spatially and the consequences of this distribution for population processes. Semivariograms and kriged maps of weed populations in several fields have helped describe spatial structure, but few generalizations can be drawn except that populations are aggregated at one or more scales. Limited information is available on the effect of weed arrangement, pattern, or field location on weed population processes. Because weeds are neither regular nor uniform in distribution, mean density alone is of limited value in estimating yield loss or describing population dynamics over a whole field. Sampling strategies that account for spatial distribution can increase sampling efficiency. Further research should focus on understanding processes that cause changes in spatial distributions over time to help predict rates of invasion and potential extent of colonization.

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Prior, C., G. Hawkes, and M. A. Berger. "Spatial scales and locality of magnetic helicity." Astronomy & Astrophysics 635 (March 2020): A95. http://dx.doi.org/10.1051/0004-6361/201936675.

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Context. Magnetic helicity is approximately conserved in resistive magnetohydrodynamic models. It quantifies the entanglement of the magnetic field within the plasma. The transport and removal of helicity is crucial in both dynamo development in the solar interior and active region evolution in the solar corona. This transport typically leads to highly inhomogeneous distributions of entanglement. Aims. There exists no consistent systematic means of decomposing helicity over varying spatial scales and in localised regions. Spectral helicity decompositions can be used in periodic domains and is fruitful for the analysis of homogeneous phenomena. This paper aims to develop methods for analysing the evolution of magnetic field topology in non-homogeneous systems. Methods. The method of multi-resolution wavelet decomposition is applied to the magnetic field. It is demonstrated how this decomposition can further be applied to various quantities associated with magnetic helicity, including the field line helicity. We use a geometrical definition of helicity, which allows these quantities to be calculated for fields with arbitrary boundary conditions. Results. It is shown that the multi-resolution decomposition of helicity has the crucial property of local additivity. We demonstrate a general linear energy-topology conservation law, which significantly generalises the two-point correlation decomposition used in the analysis of homogeneous turbulence and periodic fields. The localisation property of the wavelet representation is shown to characterise inhomogeneous distributions, which a Fourier representation cannot. Using an analytic representation of a resistive braided field relaxation, we demonstrate a clear correlation between the variations in energy at various length scales and the variations in helicity at the same spatial scales. Its application to helicity flows in a surface flux transport model show how various contributions to the global helicity input from active region field evolution and polar field development are naturally separated by this representation. Conclusions. The multi-resolution wavelet decomposition can be used to analyse the evolution of helicity in magnetic fields in a manner which is consistently additive. This method has the advantage over more established spectral methods in that it clearly characterises the inhomogeneous nature of helicity flows where spectral methods cannot. Further, its applicability in aperiodic models significantly increases the range of potential applications.

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MENSCH, JAMES. "TEMPORALITY AS A SPATIAL FIELD OF PRESENCE." HORIZON / Fenomenologicheskie issledovanija/ STUDIEN ZUR PHÄNOMENOLOGIE / STUDIES IN PHENOMENOLOGY / ÉTUDES PHÉNOMÉNOLOGIQUES 10, no. 1 (2021): 163–85. http://dx.doi.org/10.21638/2226-5260-2021-10-1-163-185.

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According to Merleau-Ponty in his Phenomenology of Perception, we experience time as a “field of presence.” In his words, “It is in my ‘field of presence’ in the widest sense […] that I make contact with time, and learn to know its course.” This field is fundamental. It elucidates my spatial apprehension. In his words: “Perception provides me with a ‘field of presence’ in the broad sense, extending in two dimensions: the here-there dimension and the past-present-future dimension. The second elucidates the first.” In other words, I understand the spatial “here-there” dimension in terms of the temporal dimension. The “there” is what I immediately grasp in still having in hand “the immediate past.” In this article, I propose to examine the general conception of time as a field of presence. This examination can be seen as a kind of “thought experiment,” where we see what happens when we reverse this relation—i.e., when we elucidate the “past-present-future dimension” in terms of the “here-there dimension.” Such a reversal, I will argue, brings to the fore the pragmatic, spatial character of lived time. Not only does it bring about a revision of horizonal structure of the field of presence, it also has consequences for psycho-analytical research.

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30

Lunga, Dalton, and Okan Ersoy. "Multidimensional Artificial Field Embedding With Spatial Sensitivity." IEEE Transactions on Geoscience and Remote Sensing 52, no. 2 (February 2014): 1518–32. http://dx.doi.org/10.1109/tgrs.2013.2251889.

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Zhdanov, G. S. "Spatial resolution of near-field optical devices." Journal of Optical Technology 71, no. 6 (June 1, 2004): 390. http://dx.doi.org/10.1364/jot.71.000390.

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Smith, J. Lleweilun, and Qimiao Si. "Spatial correlations in dynamical mean-field theory." Physical Review B 61, no. 8 (February 15, 2000): 5184–93. http://dx.doi.org/10.1103/physrevb.61.5184.

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Xue, Shutian, Antoine Barbot, and Marisa Carrasco. "Spatial frequency asymmetries around the visual field." Journal of Vision 20, no. 11 (October 20, 2020): 116. http://dx.doi.org/10.1167/jov.20.11.116.

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Escudero, Carlos. "Nonlinear field theories during homogeneous spatial dilation." Journal of Physics A: Mathematical and Theoretical 46, no. 35 (August 12, 2013): 355403. http://dx.doi.org/10.1088/1751-8113/46/35/355403.

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Boone, Marinus M., and Diemer de Vries. "Spatial sound reproduction with wave field synthesis." Journal of the Acoustical Society of America 105, no. 2 (February 1999): 933. http://dx.doi.org/10.1121/1.426306.

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Duffaut Espinosa, Luis A., Francisco Rosales, and Adolfo Posadas. "Embedding spatial variability in rainfall field reconstruction." International Journal of Remote Sensing 39, no. 9 (February 7, 2018): 2884–905. http://dx.doi.org/10.1080/01431161.2018.1433894.

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Boucher, V., and X. Nguyen Phu. "Polarization field in optical spatial vector solitons." Optics Communications 199, no. 1-4 (November 2001): 223–29. http://dx.doi.org/10.1016/s0030-4018(01)01513-9.

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Henson, D. B., S. E. Spenceley, and D. R. Bull. "Spatial classification of glaucomatous visual field loss." British Journal of Ophthalmology 80, no. 6 (June 1, 1996): 526–31. http://dx.doi.org/10.1136/bjo.80.6.526.

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Gnatchenko, S. L., K. Piotrowski, R. Szymczak, and H. Szymczak. "Field-induced spatial phase in dysprosium orthoferrite." Journal of Magnetism and Magnetic Materials 140-144 (February 1995): 2163–64. http://dx.doi.org/10.1016/0304-8853(94)01373-x.

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Castañeda, Román, and Francisco F. Medina. "Far field properties of spatial coherence beams." Optik 113, no. 3 (2002): 125–29. http://dx.doi.org/10.1078/0030-4026-00130.

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41

Abhayapala, T. D., R. A. Kennedy, and R. C. Williamson. "Spatial aliasing for near-field sensor arrays." Electronics Letters 35, no. 10 (1999): 764. http://dx.doi.org/10.1049/el:19990561.

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42

Niebauer, Christopher L., and Stephen D. Christman. "Visual Field Differences in Spatial Frequency Discrimination." Brain and Cognition 41, no. 3 (December 1999): 381–89. http://dx.doi.org/10.1006/brcg.1999.1140.

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Kishida, Masako, Daniel W. Pack, and Richard D. Braatz. "Optimal spatial field control for controlled release." Optimal Control Applications and Methods 36, no. 6 (January 19, 2015): 968–84. http://dx.doi.org/10.1002/oca.2159.

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44

Miranville, A., and R. Quintanilla. "Spatial decay for several phase-field models." ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 93, no. 10-11 (January 30, 2013): 801–10. http://dx.doi.org/10.1002/zamm.201200131.

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45

Pine, Kerrin J., Gareth R. Davies, and David J. Lurie. "Field-cycling NMR relaxometry with spatial selection." Magnetic Resonance in Medicine 63, no. 6 (April 23, 2010): 1698–702. http://dx.doi.org/10.1002/mrm.22346.

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Spitzer, H., and S. Hochstein. "A complex-cell receptive-field model." Journal of Neurophysiology 53, no. 5 (May 1, 1985): 1266–86. http://dx.doi.org/10.1152/jn.1985.53.5.1266.

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The time course of the response of a single cortical neuron to counterphase-grating stimulation may vary as a function of stimulation parameters, as shown in the preceding paper (19). The poststimulus-time histograms of the response amplitudes against time are single or double peaked, and where double peaked, the two peaks are of equal or unequal amplitudes. Furthermore, the spatial-phase dependence of cortical complex-cell responses may be a function of spatial frequency, so that the receptive field appears to have linear spatial summation at some spatial frequencies and nonlinear spatial summation at others (19). In the first part of this paper, we analyze a model receptive field that displays this behavior, and in the second part experimental data are presented and analyzed with regard to the model. The model cortical receptive field in its simplest form contains (two rows) of geniculate X-cell-like, DOG (difference-of-Gaussians)-shaped, center-surround antagonistic, circular-input subunits. We propose nonlinear summation between these two subunits, by introducing a half-wave rectification stage before pooling. The model is tested for the responses it predicts for the application of counterphase-grating stimulation. This simple model predicts the appearance of three response forms as a function of counterphase-stimulation parameters. At periodic spatial frequencies the expected-response histogram has a single peak, whose amplitude has a sinusoidal dependence on spatial phase. At spatial frequencies halfway between these, the expected-response histogram has two equal peaks whose amplitudes have a full-wave rectified sinusoidal dependence on spatial phase. At all intermediate spatial frequencies the expected-response histogram has a "mixed" form; the histogram appears sometimes with one peak, sometimes with two equal peaks, and generally with two peaks of unequal amplitude, as a function of spatial phase. Null responses are expected to appear at specific spatial phases only for the periodic spatial frequencies that give "pure" response time courses as in paragraph 5 above, and not in the more common mixed response case of paragraph 6. The analysis procedure described in the preceding paper (19) is used, separating the odd and even Fourier components of the response histograms reflecting the receptive-field intrasubunit linear summation and intersubunit nonlinear summation, respectively. We propose that this model may be used as a working hypothesis for the analysis of these aspects of the various cortical receptive-field types. Experimental data are described and discussed in terms of the model.(ABSTRACT TRUNCATED AT 400 WORDS)

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Yeung, Henry Wing Fung, Junhui Hou, Xiaoming Chen, Jie Chen, Zhibo Chen, and Yuk Ying Chung. "Light Field Spatial Super-Resolution Using Deep Efficient Spatial-Angular Separable Convolution." IEEE Transactions on Image Processing 28, no. 5 (May 2019): 2319–30. http://dx.doi.org/10.1109/tip.2018.2885236.

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BERRY, BRIAN J. L. "INTERDEPENDENCY OF SPATIAL STRUCTURE AND SPATIAL BEHAVIOR: A GENERAL FIELD THEORY FORMULATION." Papers in Regional Science 21, no. 1 (January 14, 2005): 205–27. http://dx.doi.org/10.1111/j.1435-5597.1968.tb01449.x.

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Baruch, O., and Y. Yeshurun. "The Attentional Attraction Field: Modeling spatial and temporal effects of spatial attention." Journal of Vision 10, no. 7 (August 3, 2010): 217. http://dx.doi.org/10.1167/10.7.217.

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Brodský, L., V. Vaněk, L. Borůvka, and J. Száková. "Consistency of spatial dependence of soil chemical properties in two fields: a geostatistical study." Plant, Soil and Environment 50, No. 11 (December 10, 2011): 507–12. http://dx.doi.org/10.17221/4066-pse.

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This study examined consistency of spatial variation of plant-available soil nutrients P, K, Mg and soil pH in two fields of an area of 54 and67.5 ha(haplic Luvisol and luvic Chernozem) in the region of Český Brod (Central Bohemia). Computed variograms showed a spatial dependence extending to150 mon an average with small fluctuations for most analysed data sets. These results of two different fields indicate that soil spatial variation is rather a general feature than specific to every field. However, soil available Mg in one field showed a shorter-range (89 m) and soil pH in the other showed considerably longer-range (375 m). Consistency of spatial variation features makes it possible to construct regional average and proportional variograms with great precision. This can bring further practical opportunities.

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