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Статті в журналах з теми "Spatial and temporal scaling"

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McCulloch, C. E. "Quantitative Ecology: Spatial and Temporal Scaling." Journal of Environmental Quality 24, no. 2 (March 1995): 384. http://dx.doi.org/10.2134/jeq1995.00472425002400020026x.

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Jørgensen, Sven Erik. "Quantitative ecology. Spatial and temporal scaling." Ecological Modelling 79, no. 1-3 (May 1995): 288. http://dx.doi.org/10.1016/0304-3800(95)90066-7.

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Ellis, J., and D. C. Schneider. "Spatial and temporal scaling in benthic ecology." Journal of Experimental Marine Biology and Ecology 366, no. 1-2 (November 2008): 92–98. http://dx.doi.org/10.1016/j.jembe.2008.07.012.

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Schmitz, Oliver, Elga Salvadore, Lien Poelmans, Johannes van der Kwast, and Derek Karssenberg. "A framework to resolve spatio-temporal misalignment in component-based modelling." Journal of Hydroinformatics 16, no. 4 (December 6, 2013): 850–71. http://dx.doi.org/10.2166/hydro.2013.180.

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Process-based spatio-temporal component models simulate real world processes, using encapsulated process representations that operate at individual spatial and temporal discretisations. These component models act as building blocks in the construction of multi-disciplinary, multi-scale integrated models. Coupling these independent component models, however, involves aggregation or disaggregation of the exchanged variables at model runtime, since each of the component models exposes potentially different spatial and temporal discretisations. Although conceptual methodologies for spatial and temporal scaling are available, dedicated tools that assist modellers to implement dynamic spatial and temporal scaling operations are rare. We present the accumulator, a programmable general-purpose model building block executing custom scaling operations at model runtime. We therefore characterise runtime information of input and output variables required for the implementation of scaling operations between component models with different discretisations. The accumulator is a component of an integrated modelling framework and can be completed by the modeller with custom operations for spatial and temporal scaling. To illustrate the applicability of the accumulators an integrated model is developed that couples an existing land use change model and hydrological component models at different spatial and temporal scales. The accumulators as building blocks allow modellers to construct multi-scale integrated models in a flexible manner.
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Eggert, B., P. Berg, J. O. Haerter, D. Jacob, and C. Moseley. "Temporal and spatial scaling impacts on extreme precipitation." Atmospheric Chemistry and Physics Discussions 15, no. 2 (January 23, 2015): 2157–96. http://dx.doi.org/10.5194/acpd-15-2157-2015.

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Abstract. Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space–time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.
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Chau, H. F., and K. S. Cheng. "Does spatial scaling imply temporal scaling in sandpile type cellular automata?" Physics Letters A 170, no. 3 (November 1992): 195–200. http://dx.doi.org/10.1016/0375-9601(92)91065-y.

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Lacroix, Benjamin, and Julien Dumont. "Spatial and Temporal Scaling of Microtubules and Mitotic Spindles." Cells 11, no. 2 (January 12, 2022): 248. http://dx.doi.org/10.3390/cells11020248.

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During cell division, the mitotic spindle, a macromolecular structure primarily comprised of microtubules, drives chromosome alignment and partitioning between daughter cells. Mitotic spindles can sense cellular dimensions in order to adapt their length and mass to cell size. This scaling capacity is particularly remarkable during early embryo cleavage when cells divide rapidly in the absence of cell growth, thus leading to a reduction of cell volume at each division. Although mitotic spindle size scaling can occur over an order of magnitude in early embryos, in many species the duration of mitosis is relatively short, constant throughout early development and independent of cell size. Therefore, a key challenge for cells during embryo cleavage is not only to assemble a spindle of proper size, but also to do it in an appropriate time window which is compatible with embryo development. How spatial and temporal scaling of the mitotic spindle is achieved and coordinated with the duration of mitosis remains elusive. In this review, we will focus on the mechanisms that support mitotic spindle spatial and temporal scaling over a wide range of cell sizes and cellular contexts. We will present current models and propose alternative mechanisms allowing cells to spatially and temporally coordinate microtubule and mitotic spindle assembly.
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Gebremichael, Mekonnen, and Witold F. Krajewski. "Effect of Temporal Sampling on Inferred Rainfall Spatial Statistics." Journal of Applied Meteorology 44, no. 10 (October 1, 2005): 1626–33. http://dx.doi.org/10.1175/jam2283.1.

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Abstract On the basis of temporally sampled data obtained from satellites, spatial statistics of rainfall can be estimated. In this paper, the authors compare the estimated spatial statistics with their “true” or ensemble values calculated using 5 yr of 15-min radar-based rainfall data at a spatial domain of 512 km × 512 km in the central United States. The authors conducted a Monte Carlo sampling experiment to simulate different sampling scenarios for variable sampling intervals and rainfall averaging periods. The spatial statistics used are the moments of spatial distribution of rainfall, the spatial scaling exponents, and the spatial cross correlations between the sample and ensemble rainfall fields. The results demonstrated that the expected value of the relative error in the mean rain-rate estimate is zero for rainfall averaged over 5 days or longer, better temporal sampling produces average fields that are “less noisy” spatially, an increase in the sampling interval causes the sampled rainfall to be increasingly less correlated with the true rainfall map, and the spatial scaling exponent estimators could give a bias of 40% or less. The results of this study provide a basis for understanding the impact of temporal statistics on inferred spatial statistics.
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Jarzyna, Marta A., Benjamin Zuckerberg, William F. Porter, Andrew O. Finley, and Brian A. Maurer. "Spatial scaling of temporal changes in avian communities." Global Ecology and Biogeography 24, no. 11 (August 10, 2015): 1236–48. http://dx.doi.org/10.1111/geb.12361.

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Eggert, B., P. Berg, J. O. Haerter, D. Jacob, and C. Moseley. "Temporal and spatial scaling impacts on extreme precipitation." Atmospheric Chemistry and Physics 15, no. 10 (May 29, 2015): 5957–71. http://dx.doi.org/10.5194/acp-15-5957-2015.

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Abstract. Convective and stratiform precipitation events have fundamentally different physical causes. Using a radar composite over Germany, this study separates these precipitation types and compares extremes at different spatial and temporal scales, ranging from 1 to 50 km and 5 min to 6 h, respectively. Four main objectives are addressed. First, we investigate extreme precipitation intensities for convective and stratiform precipitation events at different spatial and temporal resolutions to identify type-dependent space and time reduction factors and to analyze regional and seasonal differences over Germany. We find strong differences between the types, with up to 30% higher reduction factors for convective compared to stratiform extremes, exceeding all other observed seasonal and regional differences within one type. Second, we investigate how the differences in reduction factors affect the contribution of each type to extreme events as a whole, again dependent on the scale and the threshold chosen. A clear shift occurs towards more convective extremes at higher resolution or higher percentiles. For horizontal resolutions of current climate model simulations, i.e., ~10 km, the temporal resolution of the data as well as the chosen threshold have profound influence on which type of extreme will be statistically dominant. Third, we compare the ratio of area to duration reduction factor for convective and stratiform events and find that convective events have lower effective advection velocities than stratiform events and are therefore more strongly affected by spatial than by temporal aggregation. Finally, we discuss the entire precipitation distribution regarding data aggregation and identify matching pairs of temporal and spatial resolutions where similar distributions are observed. The information is useful for planning observational networks or storing model data at different temporal and spatial scales.
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Дисертації з теми "Spatial and temporal scaling"

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Kia, Seyed Hossein. "Uncertainty associated with scaling spectral indices of carbon fluxes at various spatial and temporal scales." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/417789/.

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Measurements from the global network of micrometeorological tower sites (FLUXNET) provide essential information on the ecosystems productivity (i.e. a key component for the study of the carbon cycle). However, the area sampled by instruments on a flux tower is poorly defined and varies with weather conditions. Additionally, gaps in the FLUXNET record are common, either due to unsuitable measurement conditions or instrument failure. Hence, remote sensing (RS) has been proposed as a way to enhance the FLUXNET database, as it provides complete spatial coverage and frequent repeat observations. In practice, the use of RS for this task is challenging. The integration of spatially-explicit ecosystem models, RS observations and eddy covariance (EC) flux measurements with environmental variables have facilitated the quantification of carbon cycling dynamics across multiple spatial and temporal scales. In this regard, process-based models with the aim of simulation of carbon dynamics in forest ecosystems are increasingly being used besides other tools to predict the effects of environmental factors on the forest carbon pool and forest productivity. However, despite this, decision makers must be aware of the limitations of these models by uncertainty analyses to make the process-based models more robust and to optimize them for estimating productivity at landscape level. There is a need to address various sources of uncertainty associated with such quantification, including sensor limitations in terms of support size defined by spatial and temporal resolutions; spatial heterogeneity of land surface properties; pre-processing calibration; and the structure of the model proposed and its parameterization. calibration; and the structure of the model proposed and its parameterization. This research investigated the sources of uncertainty mentioned across three domains of interest: spectral, spatial and temporal. The present research deals with this need using a combination of tower-based EC flux measurements and RS data from both airborne and satellite RS systems at a range of temporal and spatial scales. It incorporates multiple remote sensing data sets (Airborne LiDAR, Airborne Imaging Spectrometry, DMC, and MODIS) to derive indices related to canopy structure (nCHM), plant cover (NDVI) and photosynthesis processes (PRI), and attempts to relate these to the data measured by instruments on flux towers in two locations: Wytham Woods, southern England, and Chequamegon Nicolet National Forest in northern Wisconsin, USA. In terms of the spectral domain, the research adds to the evidence that NDVI alone is insufficient to fully characterize the primary productivity of plant canopies, specifically across heterogeneous landscape. The study also demonstrates the magnitude and variability of extraneous parameters (e.g. optical geometry, shadow fraction, soil background and aerosol) in RS observations of the mixed forest of Wytham Woods using a 3D forest light simulation model (FLIGHT model). The results reveal that the observed vegetation indices (NDVI and PRI) form the mixed forest is highly sensitive to variation in solar and view zenith angles and soil background, while the indices are relatively robust to aerosol scattering. In the temporal domain, the research makes use of a unique time-series of ten multispectral images acquired during a single growing season by the DMC satellite sensors. The heterogeneity of canopy cover has greatest impact on the DMC data early in the season, and this highlights the importance of understanding how the flux tower footprint varies with weather conditions. As the canopy began to green-up, the precision of temporal sampling became more important. Based on explicit representation of the time-varying flux tower footprint, prediction of flux tower measurements directly from space-borne coarse spatial resolution imagery is challenging and leads to a low predictive ability. In order to use the global FLUXNET EC dataset and RS observations to estimate the ecosystem productivity at regional and global scales, this research deals with an upscaling approach that it involves flux footprint climatology modelling and RS-based light use efficiency (LUE) model fusion. In this aspect, a large correlation is found between satellite-based PRI and the EC-based LUE of a homogeneous deciduous forest. However, estimating the regional level LUE of a heterogeneous landscape from space is still an uncertain process as the required spectral index (PRI) is affected by canopy level variables as well as the geometry of illumination and view. Furthermore, the sensitivity analysis of a simple Diagnostic Carbon Flux Model (DCFM) to seven input parameters (εmax, a, β, R'ref γ, λ and E0) using a five-years record of the EC data from four flux towers selected across various plant functional types (PFTs) in the Upper Midwest region of northern Wisconsin, is considered to optimize the RS-based LUE model for estimating regional productivity. The results confirm that empirical constants for the estimation of the fPAR absorbed by vegetation canopies (a and β) next to the maximum light use efficiency (εmax) has little impact on the fluctuations of net carbon exchange within each PFT whereas DCFM model was very sensitive to so, the estimation of this factor, in comparison with the other parameters, plays the key role in the accuracy of NEE's predictions. Moreover, except for homogenous canopy cover, in other PFTs, interactions among the crucial ecophysiological parameters have minor contribution to uncertainty of NEE prediction by DCFM model. In conclusion, the results demonstrated the potential combination of the satellite based approach, flux footprint modelling and data-model fusion for improving the accuracy of regional/global productivity estimations. This approach includes four steps: (1) a RS-based LUE model for estimating productivity; (2) EC flux footprint analysis for the corresponding RS images; (3) using the footprint integration of RSbased ecosystem productivity to be comparable with the tower-based EC-derived productivity values, several key parameters of the RS-based LUE model can be optimized using the DCFM; and (4) The optimized RS-based LUE model can be applied for estimating regional productivity.
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Ahongshangbam, Joyson [Verfasser]. "Tree and oil palm water use: scaling, spatial heterogeneity and temporal dynamics (Sumatra, Indonesia) / Joyson Ahongshangbam." Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2020. http://d-nb.info/122090936X/34.

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McGlinn, Daniel J. "Spatial and temporal scaling of species composition at the Tallgrass Prairie Preserve, Oklahoma implications for theory and conversation /." Click HERE to connect, 2009. http://digital.library.okstate.edu/etd/McGlinn_okstate_0664D_10364.pdf.

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Barnes, Christopher James. "Characterizing environmental, temporal and spatial scaling of Rhizosphere fungi in bioenergy crops : and their role in below-ground carbon cycling." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/72734/.

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The rhizosphere consists of plant roots and the adjoining soil, which contains a functionally and genetically rich fungal community. The obligate plant symbionts, the mycorrhizal fungi, have been shown to receive substantial quantities of plant-derived C and play an important role in belowground C dynamics. The flux and residence time of C is however likely to be highly species-specific for rhizosphere fungi, and therefore their abundance and composition will likely have important implications on C storage belowground. Rhizosphere fungal community formation is extremely complex and despite being an area of intense research, current understanding is limited. The composition and abundance of rhizosphere fungi have been shown to vary with temporal and environmental parameters, and potentially geographical separation. However, no studies to date have analysed these parameters simultaneously to isolate the independent effects of each. Clone libraries in conjunction with TRFLP were performed before progressing to 454-pyrosequencing to profile the rhizosphere fungal community of a short rotation coppice (SRC) willow filed site. In this work, distinct seasonal fungal assemblages were shown, with N availability having a large effect in summer and geographical distance effects in autumn sampling points. Additionally, a rare large transition in the composition of the rhizosphere fungi was also demonstrated, which was most likely driven by extreme rainfall earlier in the growing season of the year of transition. Finally, using ₁₃C-labelled-CO₂ the belowground movement of recently derived photo-assimilates was shown to differ between Miscanthus x giganteus and SRC willow, however no significant fluxes were associated with rhizosphere fungal pathways in either crop. Results from this work demonstrate that some of the considerable complexity of microbial communities could have between overlooked in previous community analyses, whilst the flow of C within through mycorrhizal pathways maybe less important in bioenergy cropping systems compared to other ecosystems.
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He, Qian. "Spatio-Temporal Patterns, Correlations, and Disorder in Evolutionary Game Theory." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/40296.

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Evolutionary game theory originated from the application of mathematical game theory to biological studies. Well-known examples in evolutionary game theory are the prisoner's dilemma, predator-prey models, the rock-paper-scissors game, etc. Recently, such well-known models have attracted increased interest in population dynamics to understand the emergence of biodiversity and species coexistence. Meanwhile, it has been realized that techniques from statistical physics can aid us to gain novel insights into this interdisciplinary field. In our research, we mainly employ individual-based Monte Carlo simulations to study emerging spatio-temporal patterns, spatial correlations, and the influence of quenched spatial disorder in rock-paper-scissors systems either with or without conserved total population number. In balanced rock-paper-scissors systems far away from the ``corner'' of configuration space, it is shown that quenched spatial disorder in the reaction rates has only minor effects on the co-evolutionary dynamics. However, in model variants with strongly asymmetric rates (i.e., ``corner'' rock-paper-scissors systems), we find that spatial rate variability can greatly enhance the fitness of both minor species in``corner'' systems, a phenomenon already observed in two-species Lotka-Volterra predator-prey models. Moreover, we numerically study the influence of either pure hopping processes or exchange processes on the emergence of spiral patterns in spatial rock-paper-scissors systems without conservation law (i.e., May-Leonard model). We also observe distinct extinction features for small spatial May-Leonard systems when the mobility rate crosses the critical threshold which separates the active coexistence state from an inactive absorbing state. In addition, through Monte Carlo simulation on a heterogeneous interacting agents model, we investigate the universal scaling properties in financial markets such as the fat-tail distributions in return and trading volume, the volatility clustering, and the long-range correlation in volatility. It is demonstrated that the long-tail feature in trading volume distribution results in the fat-tail distribution of asset return, and furthermore it is shown that the long tail in trading volume distribution is caused by the heterogeneity in traders' sensitivities to market risk.
Ph. D.
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Miao, Yufan. "Exploring Spatio-Temporal Patterns of Volunteered Geographic Information : A Case Study on Flickr Data of Sweden." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-15031.

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This thesis aims to seek interesting patterns from massive amounts of Flickr data in Sweden with pro- posed new clustering strategies. The aim can be further divided into three objectives. The first one is to acquire large amount of timestamped geolocation data from Flickr servers. The second objective is to develop effective and efficient methods to process the data. More specifically, the methods to be developed are bifold, namely, the preprocessing method to solve the “Big Data” issue encountered in the study and the new clustering method to extract spatio-temporal patterns from data. The third one is to analyze the extracted patterns with scaling analysis techniques in order to interpret human social activities underlying the Flickr Data within the urban envrionment of Sweden. During the study, the three objectives were achieved sequentially. The data employed for this study was vector points downloaded through Flickr Application Programming Interface (API). After data ac- quisition, preprocessing was performed on the raw data. The whole dataset was firstly separated by year based on the temporal information. Then data of each year was accumulated with its former year(s) so that the evovling process can be explored. After that, large datasets were splitted into small pieces and each piece was clipped, georeferenced, and rectified respectively. Then the pieces were merged together for clustering. With respect to clustering, the strategy was developed based on the Delaunay Triangula- tion (DT) and head/tail break rule. After that, the generated clusters were analyzed with scaling analysis techniques and spatio-temporal patterns were interpreted from the analysis results. It has been found that the spatial pattern of the human social activities in the urban environment of Sweden generally follows the power-law distribution and the cities defined by human social activities are evolving as time goes by. To conclude, the contributions of this research are threefold and fulfill the objectives of this study, respectively. Firstly, large amount of Flickr data is acquired and collated as a contribution to other aca- demic researches related to Flickr. Secondly, the clustering strategy based on the DT and head/tail break rule is proposed for spatio-temporal pattern seeking. Thirdly, the evolving of the cities in terms of human activities in Sweden is detected from the perspective of scaling. Future work is expected in major two aspects, namely, data and data processing. For the data aspect, the downloaded Flickr data is expected to be employed by other studies, especially those closely related to human social activities within urban environment. For the processing aspect, new algorithms are expected to either accelerate the processing process or better fit machines with super computing capacities.
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Rossholm, Andreas. "On Enhancement and Quality Assessment of Audio and Video in Communication Systems." Doctoral thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00604.

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The use of audio and video communication has increased exponentially over the last decade and has gone from speech over GSM to HD resolution video conference between continents on mobile devices. As the use becomes more widespread the interest in delivering high quality media increases even on devices with limited resources. This includes both development and enhancement of the communication chain but also the topic of objective measurements of the perceived quality. The focus of this thesis work has been to perform enhancement within speech encoding and video decoding, to measure influence factors of audio and video performance, and to build methods to predict the perceived video quality. The audio enhancement part of this thesis addresses the well known problem in the GSM system with an interfering signal generated by the switching nature of TDMA cellular telephony. Two different solutions are given to suppress such interference internally in the mobile handset. The first method involves the use of subtractive noise cancellation employing correlators, the second uses a structure of IIR notch filters. Both solutions use control algorithms based on the state of the communication between the mobile handset and the base station. The video enhancement part presents two post-filters. These two filters are designed to improve visual quality of highly compressed video streams from standard, block-based video codecs by combating both blocking and ringing artifacts. The second post-filter also performs sharpening. The third part addresses the problem of measuring audio and video delay as well as skewness between these, also known as synchronization. This method is a black box technique which enables it to be applied on any audiovisual application, proprietary as well as open standards, and can be run on any platform and over any network connectivity. The last part addresses no-reference (NR) bitstream video quality prediction using features extracted from the coded video stream. Several methods have been used and evaluated: Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Least Square Support Vector Machines (LS-SVM), showing high correlation with both MOS and objective video assessment methods as PSNR and PEVQ. The impact from temporal, spatial and quantization variations on perceptual video quality has also been addressed, together with the trade off between these, and for this purpose a set of locally conducted subjective experiments were performed.
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Makela, Pia K. "Spatial scaling in human peripheral vision." Thesis, Aston University, 1994. http://publications.aston.ac.uk/14603/.

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The observation that performance in many visual tasks can be made independent of eccentricity by increasing the size of peripheral stimuli according to the cortical magnification factor has dominated studies of peripheral vision for many years. However, it has become evident that the cortical magnification factor cannot be successfully applied to all tasks. To find out why, several tasks were studied using spatial scaling, a method which requires no pre-determined scaling factors (such as those predicted from cortical magnification) to magnify the stimulus at any eccentricity. Instead, thresholds are measured at the fovea and in the periphery using a series of stimuli, all of which are simply magnified versions of one another. Analysis of the data obtained in this way reveals the value of the parameter E2, the eccentricity at which foveal stimulus size must double in order to maintain performance equivalent to that at the fovea. The tasks investigated include hyperacuities (vernier acuity, bisection acuity, spatial interval discrimination, referenced displacement detection, and orientation discrimination), unreferenced instantaneous and gradual movement, flicker sensitivity, and face discrimination. In all cases tasks obeyed the principle of spatial scaling since performance in the periphery could be equated to that at the fovea by appropriate magnification. However, E2 values found for different spatial tasks varied over a 200-fold range. In spatial tasks (e.g. bisection acuity and spatial interval discrimination) E2 values were low, reaching about 0.075 deg, whereas in movement tasks the values could be as high as 16 deg. (DX 185,687)
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Cary, Ariel. "Scaling Geospatial Searches in Large Spatial Databases." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/548.

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Modern geographical databases store a rich set of aspatial attributes in addition to geographic data. Retrieving spatial records constrained on spatial and aspatial attributes provides users the ability to perform more interesting spatial analyses via composite spatial searches; e.g., in a real estate database, "Find the nearest homes for sale to my current location that have backyard and whose prices are between $50,000 and $80,000". Efficient processing of such composite searches requires combined indexing strategies of multiple types of data. Existing spatial query engines commonly apply a two-filter approach (spatial filter followed by non-spatial filter, or viceversa), which can incur large performance overheads. On the other hand, the amount of geolocation data in databases is rapidly increasing due in part to advances in geolocation technologies (e.g., GPS- enabled mobile devices) that allow to associate location data to nearly every object or event. Hence, practical spatial databases may face data ingestion challenges of large data volumes. In this dissertation, we first show how indexing spatial data with R-trees (a typical data pre- processing task) can be scaled in MapReduce – a well-adopted parallel programming model, developed by Google, for data intensive problems. Close to linear scalability was observed in index construction tasks over large spatial datasets. Subsequently, we develop novel techniques for simultaneously indexing spatial with textual and numeric data to process k-nearest neighbor searches with aspatial Boolean selection constraints. In particular, numeric ranges are compactly encoded and explicitly indexed. Experimental evaluations with real spatial databases showed query response times within acceptable ranges for interactive search systems.
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Winstral, Adam. "Spatial scaling of snow processes : modelling implications." Thesis, University of Reading, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553176.

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Snow cover affects life on Earth in many important ways. The high reflectivity and high moisture content of snow cover affects the global energy balance, atmospheric circulation, and weather. The characteristic heterogeneity of ephemeral mountain snowpacks exhibits strong controls on hydrological, biological, and ecological processes. Accurately predicting process responses is based on knowing the volume, distribution, and state of the snow cover. Physically-based distributed snow models (DSMs) are capable of explicitly representing these vital heterogeneities and are well suited for predicting future impacts such as those associated with climate change. These models however, are currently limited by high computational demands. This research sought to reduce these computational demands and extend the limits of physically-based DSMs. In many regions, wind plays a dominant role in determining snow accumulation patterns .: New algorithms based on terrain and vegetation structure were developed that capably reproduced observed heterogeneities in mountain winds and wind-affected snow distributions. Characterizing the wind and snow patterns in this simplified manner bypassed the heavy computational demands associated with numerically solving the fluid mechanics of windflow and mass transport. The algorithms were incorporated into a mass and energy balance DSM which accurately depicted the heterogeneous accumulation and melt of the snow cover. The computational efficiency of these new algorithms enabled what was perhaps the first DSM application to include the effects of blowing and drifting snow over this large an area at this fine a temporal resolution. Model scale also plays an important role in determining computation times. It was shown that a 100 metre model scale was sufficient for characterizing mountain snow distributions and melt. Furthermore, it was determined that not all the driving processes required the same level of detail creating the potential for additional cost savings. The presented findings have substantially reduced costs and expanded the capabilities of DSMs.
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Книги з теми "Spatial and temporal scaling"

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Schneider, David C. Quantitative ecology: Spatial and temporal scaling. San Diego: Academic Press, 1994.

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2

Quattrochi, Dale A. Spatial and temporal scaling of thermal infrared remote sensing data. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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3

Stock, Oliviero, ed. Spatial and Temporal Reasoning. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-0-585-28322-7.

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4

Oliviero, Stock, ed. Spatial and temporal reasoning. Dordrecht: Kluwer Academic Publishers, 1997.

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5

Stock, Oliviero. Spatial and Temporal Reasoning. Dordrecht: Springer, 1997.

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6

Roddick, John F., and Kathleen Hornsby, eds. Temporal, Spatial, and Spatio-Temporal Data Mining. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45244-3.

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7

Ligozat, Gérard. Qualitative Spatial and Temporal Reasoning. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118601457.

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8

Lovett, Sarah Breen. Expanded architecture: Temporal spatial practices. Braunach, Germany: Spurbuchverlag, 2016.

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9

Ligozat, Gérard. Qualitative spatial and temporal reasoning. London, UK: ISTE, 2011.

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10

Makela, Pia Kristiina. Spatial scaling in human peripheral vision. Birmingham: Aston University. Department of Vision Science, 1994.

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Частини книг з теми "Spatial and temporal scaling"

1

Parisi, Francesco, Austin Parker, John Grant, and V. S. Subrahmanian. "Scaling Cautious Selection in Spatial Probabilistic Temporal Databases." In Methods for Handling Imperfect Spatial Information, 307–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14755-5_12.

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Tobin, Patrick C., Kyle J. Haynes, and Allan L. Carroll. "Spatial Dynamics of Forest Insects." In Forest Entomology and Pathology, 647–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-11553-0_18.

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AbstractThe study of the spatial dynamics of forest insects has a long history, and many forest insect species have served as model systems for studying conceptual processes of population biology and ecology. Because forest insect population data were often collected from georeferenced locations, even prior to the development of geodatabases and spatial statistical software, they provide an important historical resource for understanding insect population dynamics and changes in those dynamics through time. Advances in spatial statistics have furthermore enabled forest entomologists to consider forest insect dynamics over multiple spatial and temporal scales, and vast spatial and temporal extents. In this chapter, we first introduce the importance of scaling in studies of spatial dynamics, and review spatial pattern formation in forest insect populations. We conclude the chapter by addressing metapopulation dynamics, and the concept of spatial synchrony in outbreaking forest insects.
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3

Geiger, Cathleen A., and Mark R. Drinkwater. "Impact of Temporal-Spatio Resolution on Sea-Ice Drift and Deformation." In IUTAM Symposium on Scaling Laws in Ice Mechanics and Ice Dynamics, 407–16. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9735-7_34.

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Gutierrez, Angelica Garcia, and Peter Baumann. "Using Preaggregation to Speed Up Scaling Operations on Massive Spatio-temporal Data." In Conceptual Modeling – ER 2010, 188–201. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16373-9_14.

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Ghosh, Shreya, and Jaydeep Das. "Dynamic Voltage and Frequency Scaling Approach for Processing Spatio-Temporal Queries in Mobile Environment." In Green Mobile Cloud Computing, 185–99. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08038-8_9.

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Winkelmann, Stefanie, and Christof Schütte. "Temporal Scaling." In Stochastic Dynamics in Computational Biology, 105–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62387-6_3.

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Winkelmann, Stefanie, and Christof Schütte. "Spatial Scaling." In Stochastic Dynamics in Computational Biology, 131–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62387-6_4.

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Sy, Bon K., and Arjun K. Gupta. "Temporal-Spatial Data." In The Kluwer International Series in Engineering and Computer Science, 83–91. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9001-3_6.

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Palacios, Antonio. "Spatial-Temporal Models." In Mathematical Engineering, 363–430. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04729-9_8.

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Franklin, Nancy, and Todd Federico. "Organization of Temporal Situations." In Spatial Language, 103–20. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-015-9928-3_6.

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Тези доповідей конференцій з теми "Spatial and temporal scaling"

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Schmoll, Sebastian, Sabrina Friedl, and Matthias Schubert. "Scaling the Dynamic Resource Routing Problem." In SSTD '19: 16th International Symposium on Spatial and Temporal Databases. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3340964.3340983.

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2

Filion, Y. R., Z. Li, and S. G. Buchberger. "Temporal and Spatial Scaling of Instantaneous Residential Water Demand for Network Analysis." In World Environmental and Water Resources Congress 2007. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40927(243)512.

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Tesfaye Demissie, Daniel E. Storm, Mark E. Payton, Michael D. Smolen, Nicholas T. Basta, Hailin Zhang, and Miguel L. Cabrera. "SPATIAL AND TEMPORAL SCALING EFFECTS ON HYDROLOGY AND PHOSPHORUS LOSS IN RUNOFF FROM PASTURES." In 2004, Ottawa, Canada August 1 - 4, 2004. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2004. http://dx.doi.org/10.13031/2013.16448.

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4

Igarashi, Ko, and Seiichiro Katsura. "Spatial shaping of motion-data based on motion-copying system using variable temporal scaling." In IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2014. http://dx.doi.org/10.1109/iecon.2014.7048915.

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5

Hutchings, Jennifer K., Cathleen Geiger, Andrew Roberts, Jacqueline Richter-Menge, and Bruce Elder. "On the Spatial and Temporal Characterization of Motion Induced Sea Ice Internal Stress." In SNAME 9th International Conference and Exhibition on Performance of Ships and Structures in Ice. SNAME, 2010. http://dx.doi.org/10.5957/icetech-2010-166.

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In April 2007 an array of buoys was deployed in the Beaufort Sea with one aim (among others) of examining the relationship between internal ice stress and ice pack strain-rate or deformation. Here we present preliminary analysis of stress data from this experiment. This analysis is discussed in the context of strain-rate analysis that has been performed previously. In order to identify ice motion induced stress from stress measurements recorded at a point in the ice pack, we first need to remove the thermal stress signal from the measurement time series. We introduce a conceptual model of thermal stresses to support a method of extracting ice motion induced stress from stress buoy data. The model will require independent verification, which we outline, however is useful for understanding our results. In this paper we focus on spectral and scaling analysis of ice motion induced stresses, and compare these to similar analysis of sea ice strain-rate. By comparing spectral properties of stress and divergence we estimate that dynamic stress events (such as ridge building) may be felt at a stress sensor up to 45km from the site of deformation. Ice motion induced stresses demonstrate fractal scaling properties, and are anti-persistent. This echoes similar results that have been identified for sea ice strain rate across spatial scales from 10 to 1000 km. Ice motion induced stress and sea ice strain rate can not be described by Gaussian statistics, and have “fat tailed” probability distribution functions. These findings provide insight into how to model risk of large deformation, with large ice motion induced stress, events impacting any given place in the Arctic ice pack.
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6

Potapov, Alexander A., Weiping Liu, Vitaliy A. German, Tianhua Feng, and Sergo Sh Rekhviashvili. "Fractal-Scaling Non-Parametric Processing of Spatial-Temporal Flow of Real Polarimetric Information in the Radio Systems." In 2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS). IEEE, 2019. http://dx.doi.org/10.1109/icicas48597.2019.00095.

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7

Syed, Arslan Ali, Yunfei Zhang, and Klaus Bogenberger. "Data-Driven Spatio-Temporal Scaling of Travel Times for AMoD Simulations." In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2023. http://dx.doi.org/10.1109/itsc57777.2023.10422313.

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8

Abramov, Israel, and James Gordon. "Color appearance in central and peripheral retina." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.tub1.

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Cone and ganglion cell densities fall rapidly with eccentricity from the fovea. But the decline is not symmetrical: cell densities decrease more rapidly on the temporal retina. We examined the implications of this spatial organization for color vision. Spectral lights were presented along the horizontal meridian from 40° nasal to 40° temporal. Several stimulus sizes were used to identify the minimal size for best color vision at each retinal locus. Color vision was assessed by means of hue and saturation scaling. Multidimensional scaling was then used to derive uniform appearance diagrams from the data. These diagrams illustrate the color spaces associated with each size-location combination; we also derived discrimination functions from them. As expected from retinal anatomy, peripheral stimuli had to be progressively enlarged to maintain a full range of saturated hues; this enlargement had to be greater in temporal retina to produce comparable sensations to those from the corresponding nasal locations. Small stimuli produced restricted color spaces akin to those of tritanlike deficits. Variations in cone destiny alone cannot account for the changes in color vision across the visual field.
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9

Lehotai, Levente, Szabolcs Tóth, Viktor Pajer, Imre Seres, János Csontos, Ádám Börzsönyi, Károly Osvay, et al. "Advanced numerical simulation of high energy thin plate post-compression in 3+1D." In Advanced Solid State Lasers. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/assl.2022.jw3a.9.

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Energy scaling of the thin-plate post-compression technique was investigated with pulse energies up to 10 J by utilizing a novel 3+1D numerical simulation environment, with special focus on the few-to-single-cycle temporal regime and spatio-temporal couplings.
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10

Lokk, Reinar, Mirjam Blokker, Joby Boxall, Michele Romano, Anna Provost, and Stewart Husband. "The impact of drinking water network model spatial and temporal scale on hydraulic metrics indicating discolouration risk." In 2nd WDSA/CCWI Joint Conference. València: Editorial Universitat Politècnica de València, 2022. http://dx.doi.org/10.4995/wdsa-ccwi2022.2022.14084.

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Matching model complexity to application and ensuring sufficient complexity to capture the emergent behaviour of interest is a perennial challenge. In this paper we define a model as the variables, parameters and factors that represent a particular place, time and situation, not the software or algorithms. Specifically, we explore the cross products of spatial and temporal scaling of water demands within extended period 1D network model simulations to predict the hydraulic conditions within individual drinking water pipes and the association of this with discolouration risk. High spatial scale hydraulic models investigated include mapping each customer with a unique demand node instead of the current practice of aggregated demand to nodes at the ends of pipe lengths. For demand profiling we compare top-down DMA inlet patterns at 15-minute resolution with bottom-up stochastic demand patterns down to 1 second timesteps. The value of the resulting increases in resolution of hydraulic model outputs are captured in a range of pipe specific metrics that are likely to be indicative of discolouration risk. Unlike water quality surrogate of water age or chlorine residual that aggregate time and pipe effects from source to point of interest, discolouration risk has been shown to be primarily a function of the hydraulic conditions in a specific length of pipe. Hence the additional effort to achieve high-resolution modelling simulations are perhaps warranted to manage discolouration. Results review proposed discolouration metrics by correlating with consumer reported discolouration events, showing how these change as a function of spatial and temporal resolution. For example, increasing temporal scale from 15 minutes to 1-minute results in a 15-fold increase in identifying flow reversal locations that can facilitate settling of network discolouration material and therefore pose a discolouration risk. High temporal scale is shown to capture the on/off nature of customer demands and the significant impact on peak velocities that are shown suppressed when using aggregated profiles. This work provides an indication of the optimal level of model resolution required to differentiate pipes according to discolouration risk and hence improve targeting of pro-active maintenance and discolouration management efficiency.
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Звіти організацій з теми "Spatial and temporal scaling"

1

Sohane, Nidhi, Ruchika Lall, Ashwatha Chandran, Rasha Hasan Lala, Namrata Kapoor, and Harshal Deepak Gajjar. Home as Workplace: A Spatial Reading of Work-Homes. Indian Institute for Human Settlements, 2021. http://dx.doi.org/10.24943/hwsrwh10.2021.

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When home serves as workplace, the interface of domestic and productive spheres has spatial and social effects on various users of the space, scaling at times to the neighbourhood and the city. This study looks at all the ways in which home aids work — spatially and infrastructurally — and illustrates the role of various factors and actors in engaging with and shaping the work-home boundary. Work-homes in the Global South often engage transversally with formal planning. Users of work-homes exercise their agency in complex ways to maneuver the work-home boundary, often making post-facto modifications to the work-home. The study collates a repository of spatial and temporal innovation strategies devised by users to balance domestic and productive spheres in their homes, as a site to derive lessons for planning, housing policy and architecture. It investigates the role of the state in spatially enabling or limiting work-homes, and using the Indian context as an illustrative example, suggests enabling frameworks in planning that address the spatial particularities of work-homes
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2

Williams, H. Chapter 2: Temporal and spatial divisions. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1995. http://dx.doi.org/10.4095/205246.

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3

Griffiths, Hugh. Bistatic Denial Using Spatial-Temporal Coding. Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada387730.

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4

Swinney, H. L. Complex temporal and spatial patterns in nonequilibrium systems. Office of Scientific and Technical Information (OSTI), September 1991. http://dx.doi.org/10.2172/5053202.

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5

Mobley, Curtis D., and Robert A. Maffione. Spatial and Temporal Measurements of Benthic Optical Properties. Fort Belvoir, VA: Defense Technical Information Center, April 1999. http://dx.doi.org/10.21236/ada362432.

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Maffione, Robert A. Spatial and Temporal Measurements of Benthic Optical Properties. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada627748.

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7

Maffione, Robert A. Spatial and Temporal Measurements of Benthic Optical Properties. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada630455.

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8

Maffione, Robert A. Spatial and Temporal Measurements of Benthic Optical Properties. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada635926.

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McKenna, Sean Andrew, and Karen A. Gutierrez. Spatial-temporal event detection in climate parameter imagery. Office of Scientific and Technical Information (OSTI), October 2011. http://dx.doi.org/10.2172/1029771.

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Niemann, Jeffrey D. Scaling Properties and Spatial Interpolation of Soil Moisture. Fort Belvoir, VA: Defense Technical Information Center, August 2004. http://dx.doi.org/10.21236/ada426497.

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