Spatio-temporal Measure Research Articles

Short Spatiotemporal Fire History Explains the Occurrence of Beetles Favoured by Fire.

The number and area of forest fires in northern Europe have been dramatically reduced during the past century, and several fire-favoured species are now threatened. To promote the recovery of these species, prescribed burning is often used as a conservation measure, and to optimise the use of these conservation burns, knowledge is needed on suitable fire frequency, size and placement in the landscape. The aim of this study was to analyse the effect of recent fire history (12 yrs) on beetles sampled using smoke attraction traps at 21 forest sites in a 10,000 km2 region. We analysed the odds of finding a fire-favoured beetle species or individual among the beetles in each trap using a new spatiotemporal connectivity measure and compared the results to non-fire-favoured and saproxylic species. For fire-favoured beetles, both the number of species and individuals significantly increased with connectivity to previous fires, while the other two groups did not. The spatiotemporal connectivity that best explained the patterns suggests that fire-favoured beetles mainly respond to fires within a 2 km range up to 2-3 years after the fire. Hence, to preserve fire-favoured insects, prescribed fires must be close in space and time to other fires-whether prescribed or natural.

The interpersonal coordination constraint on the volleyball setter’s decision-making on setting direction

This study investigated the setter’s decision-making on setting direction based on interpersonal (interaction between players) and extra personal (interaction between players and some place or object) coordination. The sample consisted of 86 sequences of play involving settings performed by males (n = 43) and females (n = 43). Fifty-nine spatiotemporal measures of interpersonal and extra personal coordination were obtained from the x and y coordinates of volleyball players’ displacements using the TACTO software. Settings to each court zone were compared in relation to each spatiotemporal measure. Results showed that when the final area between attacker in the zone 3 and block was greatest and emerged from highest velocity, setters decided to set to zone 2. On the other hand, when the foregoing area was smallest and emerged from lowest velocity, setters decided to set to zones 3 and 4. It was concluded that the final area between attacker in the zone 3 and block and its emerging velocity constrained the setters’ decision-making on setting direction. This study provides useful insights into the design of practice tasks in volleyball, suggesting that setters should be advised to be attuned to the interpersonal coordination involving attacker in the zone 3 and block.

How athletes’ biomechanical running characteristics effect running economy during the use of running shoes with and without carbon inserts

To maximise running economy (RE), shoe manufacturers placed carbon plates within the midsole of shoes. Shoe technology research is limited on understanding the variability of individual responses to carbon-plated shoes and how these responses vary across running velocities. Little research on same shoe characteristics with and without a stiff element has been completed. This study aimed to investigate how running shoes with carbon versus without a carbon composite stiff element alter individual running biomechanics and the metabolic cost of running. Ethical approval was gained from Cardiff Metropolitan University Ethics Committee. Ten male athletes (69 ± 9 kg; 174 ± 4 cm; 28 ± 9 years) completed two submaximal incremental treadmill runs. One test was completed in a shoe without carbon (C1), the other test was completed in carbon shoes (C2), the order of testing for each shoe were randomised. Running velocity started at 9 km/h and increased by 1 km/h every four mins, blood lactate samples were taken after every stage. Once 4 mmol·L−1 (OBLA; the second lactate turn point) had been reached one more stage was completed. Gas exchange was analysed throughout the whole test. The first 15 s of the final 2 minutes of each stage was recorded using Theia3D markerless motion capture software (Theia3Dv2022.1.0.2309, Theia Markerless, Inc., Kingston, ON, Canada). Data were analysed in 4 stages, the initial stage, pre-OBLA, OBLA and post-OBLA. Physiology data were averaged over the final two mins of each stage. Discrete joint angles were taken from each stage, and an average of the 15 s recording was taken for spatiotemporal measure. Data were analysed using a four-way repeat measures ANOVA, to show individual differences. Non-parametric data were analysed using Wilcoxon signed-rank test. Hedges g calculations were completed to calculate effect size (ES). Results showed significant increase in flight time (FT; P = 0.04, ES = 0.20) in the pre-OBLA stage when using C2. Metatarsophalangeal joint (MTP) dorsiflexion showed significant increase during the initial stage in C2 (P = 0.05, ES = 0.8), and ankle dorsiflexion had significant increase in the post-OBLA stage in C2 (P = 0.03, ES = 0.2). The were no significant differences present in the physiology data. Across the physiological, spatiotemporal and kinematics, high dispersions around the mean were exhibited. Findings suggest that to improve RE, mechanical and spatiotemporal changes need to be present when using C2. Further findings show carbon shoes elicit highly individual responses to both RE and mechanics of running.

Measuring Diffusion Over a Large Network

Abstract This article introduces a measure of the diffusion of binary outcomes over a large, sparse network, when the diffusion is observed in two time periods. The measure captures the aggregated spillover effect of the state-switches in the initial period on their neighbours’ outcomes in the second period. This article introduces a causal network that captures the causal connections among the cross-sectional units over the two periods. It shows that when the researcher’s observed network contains the causal network as a subgraph, the measure of diffusion is identified as a simple, spatio-temporal dependence measure of observed outcomes. When the observed network does not satisfy this condition, but the spillover effect is non-negative, the spatio-temporal dependence measure serves as a lower bound for diffusion. Using this, a lower confidence bound for diffusion is proposed, and its asymptotic validity is established. The Monte Carlo simulation studies demonstrate the finite sample stability of the inference across a range of network configurations. The article applies the method to data on Indian villages to measure the diffusion of microfinancing decisions over households’ social networks.

A Novel Non-Parametric Spatiotemporal Scan Statistic: An Application to Detect Disease Outbreaks

The majority of the widely used scan statistics are based on distributional assumptions. Contrary to the existing methods, with a new perspective in clustering, the Mann-Whitney Scan Statistic was introduced to detect clusters in continuous data indexed by time or space, without any distributional assumptions or parameters to set up. We propose an extension of the Mann-Whitney Scan Statistic that can be applied to spatiotemporal data based on spatiotemporal distance measure. This novel scan statistic is distribution-free and seems to be powerful against parametric spatiotemporal scan statistics. The results are applicable in a wide variety of spatiotemporal domains, including epidemiology, socioeconomic analysis and climate sciences, irrespective of continuous or discrete data.

GsstSIM: A high‐performance and synchronized similarity analysis method of spatiotemporal trajectory based on grid model representation

AbstractExisting spatiotemporal similarity analysis methods for trajectories have the problems of spatiotemporal unsynchronization and low efficiency in processing large‐scale datasets, which cannot satisfy the increasingly urgent requirements of real‐time or quasi‐real‐time applications. To address these problems, this article proposes a grid‐based and synchronized spatiotemporal similarity analysis method based on the spatiotemporal grid model called gsstSIM. First, a low‐dimensional and multi‐scale trajectory coding representation is implemented based on the spatiotemporal grid model. Second, a synchronized spatiotemporal similarity measure is proposed based on trajectory codes. It transforms the similarity analysis from complex geometric calculations to simple algebraic operations of code sets, which reduces the computational complexity. In addition, the trajectory encoding representation with space‐time collinearity enables gsstSIM to measure the synchronized spatiotemporal similarity. Third, the efficient Multi‐scale grid index, called MSGrid, is established to realize fast query of top‐K similar trajectories for large‐scale datasets. Experimental results demonstrate that gsstSIM is more robust to noise positioning points and various sampling rates than the state‐of‐the‐art algorithms STLCSS, TWS and SWS. It can achieve a second‐level response of spatiotemporal similarity query in processing large‐scale datasets, which is much faster than existing algorithms. The proposed method has promising to support the applications with high time‐efficiency requirements such as epidemic tracking and traffic condition calculation.

Weighted Brain Network Analysis on Different Stages of Clinical Cognitive Decline.

This study addresses brain network analysis over different clinical severity stages of cognitive dysfunction using electroencephalography (EEG). We exploit EEG data of subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) patients and Alzheimer’s disease (AD) patients. We propose a new framework to study the topological networks with a spatiotemporal entropy measure for estimating the connectivity. Our results show that functional connectivity and graph analysis are frequency-band dependent, and alterations start at the MCI stage. In delta, the SCI group exhibited a decrease of clustering coefficient and an increase of path length compared to MCI and AD. In alpha, the opposite behavior appeared, suggesting a rapid and high efficiency in information transmission across the SCI network. Modularity analysis showed that electrodes of the same brain region were distributed over several modules, and some obtained modules in SCI were extended from anterior to posterior regions. These results demonstrate that the SCI network was more resilient to neuronal damage compared to that of MCI and even more compared to that of AD. Finally, we confirm that MCI is a transitional stage between SCI and AD, with a predominance of high-strength intrinsic connectivity, which may reflect the compensatory response to the neuronal damage occurring early in the disease process.

Spatiotemporal distribution and control measure evaluation of droplets and aerosol clouds in dental procedures.

We evaluated the distributions of dental splatters and the corresponding control measure effects with high-speed videography and laser diffraction. Most of the dental splatters were small droplets (<50 μm). High-volume evacuation combined with a suction air purifier could clear away most of the droplets and aerosols.

Recommendation system for climate informed urban design under model uncertainty

We develop a novel recommendation system for optimal urban design from a socio-economic and Outdoor Thermal Comfort (OTC) perspectives. Currently, urban planners and designers do not have quantitative tools or methods at their disposal to incorporate various important effects into consideration in a systematic way. Our framework is based on risk measures which quantify and take into account various important design criteria such as OTC, spatial use in the form of exposure maps and the investment cost of the design. Our framework combines those criteria into a spatio-temporal risk measure to assess the performance of candidate urban design options. This is used as the basis for our optimal design problem formulation. We then formulate the problem as an optimisation problem which is easy to solve and has a clear interpretation. The objective of this paper is therefore twofold: on the one hand, we develop technical knowledge and methodologies to assist urban planners develop and prioritize competing urban design strategies. On the other hand, we demonstrate the importance of incorporating the uncertainty in climate models into the utility function when making policy decisions. To illustrate how our framework can be used in practice we present a real-world study, which is based on a set of urban design strategies that aim to improve the OTC of a specific site in Singapore. The ENVI-met micro-climate model has been used in order to calculate the spatio-temporal OTC process. We show how our framework can assist decision-makers make more informed and interpretable choices on how to select the optimal design option and where to allocate best their investment/resources.

Spatiotemporal multi-disease transmission dynamic measure for emerging diseases: an application to dengue and zika integrated surveillance in Thailand

BackgroundNew emerging diseases are public health concerns in which policy makers have to make decisions in the presence of enormous uncertainty. This is an important challenge in terms of emergency preparation requiring the operation of effective surveillance systems. A key concept to investigate the dynamic of infectious diseases is the basic reproduction number. However it is difficult to be applicable in real situations due to the underlying theoretical assumptions.MethodsIn this paper we propose a robust and flexible methodology for estimating disease strength varying in space and time using an alternative measure of disease transmission within the hierarchical modeling framework. The proposed measure is also extended to allow for incorporating knowledge from related diseases to enhance performance of surveillance system.ResultsA simulation was conducted to examine robustness of the proposed methodology and the simulation results demonstrate that the proposed method allows robust estimation of the disease strength across simulation scenarios. A real data example is provided of an integrative application of Dengue and Zika surveillance in Thailand. The real data example also shows that combining both diseases in an integrated analysis essentially decreases variability of model fitting.ConclusionsThe proposed methodology is robust in several simulated scenarios of spatiotemporal transmission force with computing flexibility and practical benefits. This development has potential for broad applicability as an alternative tool for integrated surveillance of emerging diseases such as Zika.

Access and egress times to high-speed rail stations: a spatiotemporal accessibility analysis

Accessibility by high-speed rail (HSR) depends not only on station-to-station travel time, but also on access and egress times, which can be determining factors in total journey travel time. However, studies focusing on accessibility analyses of access/egress times to/from stations are less extended in the literature and centre mainly on the influence of access times to stations on HSR accessibility levels on a regional scale. This paper's aim is to evaluate the importance of access and egress times to/from HSR stations in an urban context. We carry out a spatiotemporal accessibility analysis that considers the temporal variations of both taxi and public transport travel times. General Transit Feed Specification (GTFS) files for public transport and TomTom Speed Profiles data for cars are used to measure access/egress times. These kinds of data allow for the calculation of travel times from/to HSR stations through network analysis GIS tools at different times of the day, and thus a spatiotemporal accessibility measure can be obtained. This accessibility measure is complemented by a mass factors representing the activity ‘hotspots’ in the visited city throughout the workday, which is derived from Twitter data, while population is considered for city of residence. This method was applied to the two largest metropolitan areas in Spain: Madrid and Barcelona, where the influence of access/egress times acquires a higher relevance for rail-based trips. The results obtained show that access and egress times vary significantly during the day, depending on the levels of traffic congestion and the frequency of public transport services, which are always more favourable for taxis. In addition, weighted average access and egress times at the home end are higher than those at the activity end since population tends to show more dispersed spatial patterns than activities. Another interesting finding is that the first and last mile of the HSR trip usually account for a high percentage increase in travel time (about 35% for taxis and 55% for public transport, respectively). These results have important policy implications. The paper suggests that HSR accessibility can be improved also by improving local transport services, scheduling coordination and land use policies.

The impact of driver’s license ownership on unemployed job seekers’ access to job openings: Assessing the driver’s license at School project in Flanders

An inefficient accessibility to the labor market is considered as one of the key threats to a region’s economic wellbeing. However, the high dominance of and independency on travel by private motorized vehicle related to the post-war emergence of the automobile industry has led to various spatial mismatches between living locations and the labor market. Consequently, unemployed job seekers’ inability to find a suitable job is strongly interwoven with transport-related issues, and more specifically, with having a driver’s license. The research aims to examine the impact of the policy decision to discontinue the ‘Driver’s License at School’ project, which currently provides secondary school pupils (aged 17 years or older) with the ability to obtain their theoretical driver’s license at a diminished rate. This is examined through the assessment of job seeker’s accessibility to job vacancies in the region of Flanders (and, in extension, the Brussels Capital Region). Therefore, a spatio-temporal accessibility measure was constructed to identify the number of job opportunities per traffic analysis zone for different transport modes, while considering job competition. The results show that job seekers with a driver’s license have a higher accessibility to job opportunities than those without. Moreover, significant relationships exist between job seekers’ accessibility and their socio-demographic characteristics. The study argues that – although laudable from an environmental perspective – the discontinuation of the project will lead to various inequitable outcomes for certain groups. This has important ramifications for transport policies focusing on equity in job accessibility as well as spatial planning policies that address how the future Flemish urban landscape should ideally evolve. In addition, it fuels the debate on the discrepancy between sustainable transport policies and an equitable distribution of transport benefits.

A spatio-temporal accessibility measure for modelling activity participation in discretionary activities

Accessibility is a key indicator for the number of opportunities experienced by an individual, and it is generally assumed that higher levels of accessibility lead to higher levels of activity participation and satisfaction. Despite the fact that this relationship has been tested in preceding studies, no clear pattern of correlation has been found between an individual’s accessibility and his/her participation in out-of-home discretionary activities. Previous studies mostly applied aggregate, spatial accessibility measures that do not account for the heterogeneity related to an individual’s spatio-temporal constraints. However, in addition to locations’ spatial distribution, personal constraints related to the mandatory activities a person undertakes – and therefore, his/her available time budget throughout the day – impact activity choices and scheduling. This paper proposes a disaggregate, person-based accessibility measure that takes spatial and temporal constraints into consideration for the travel behavior of 11,599 individuals in the Wasatch Front region, Utah. This method is compared to an aggregate, home-based accessibility measure to assess both methods’ ability to predict activity participation. The results show a highly significant, moderate correlation between the proposed person-based accessibility measure and participants’ surveyed partaking in discretionary activities. Both the model prediction and the locally weighted regression smoother indicate that the greatest change in participation occurs within the mid-range of accessibility levels, and not in the low end of the accessibility range as was expected. In addition, the home-based method shows a negative and highly significant relationship to activity participation, which indicates that aggregate accessibility measures may provide counterintuitive findings.

Kinematic Analysis of Speech Sound Sequencing Errors Induced by Delayed Auditory Feedback.

Delayed auditory feedback (DAF) causes speakers to become disfluent and make phonological errors. Methods for assessing the kinematics of speech errors are lacking, with most DAF studies relying on auditory perceptual analyses, which may be problematic, as errors judged to be categorical may actually represent blends of sounds or articulatory errors. Eight typical speakers produced nonsense syllable sequences under normal and DAF (200 ms). Lip and tongue kinematics were captured with electromagnetic articulography. Time-locked acoustic recordings were transcribed, and the kinematics of utterances with and without perceived errors were analyzed with existing and novel quantitative methods. New multivariate measures showed that for 5 participants, kinematic variability for productions perceived to be error free was significantly increased under delay; these results were validated by using the spatiotemporal index measure. Analysis of error trials revealed both typical productions of a nontarget syllable and productions with articulatory kinematics that incorporated aspects of both the target and the perceived utterance. This study is among the first to characterize articulatory changes under DAF and provides evidence for different classes of speech errors, which may not be perceptually salient. New methods were developed that may aid visualization and analysis of large kinematic data sets. https://doi.org/10.23641/asha.5103067.

Development of a spatiotemporal composite measure of climate change-related human health effects in urban environments: a Metro Vancouver study

BackgroundRapid population growth along with an increase in the frequency and intensity of climate change-related effects in coastal urban environments emphasise the need for the development of new instruments to help disaster planners and policy makers to select and prioritise mitigation and adaptation measures. The concept of the resilience of a community, which is a measure of how rapidly the community can recover to its previous level of functionality following a disruptive event is still a relatively new concept for many engineers, planners, and policy makers, but is becoming recognised as an increasingly important, and, some would argue, essential component for the development and subsequent assessment of adaptation plans being considered for communities at risk of climate change-related events. The holistic approach, which is the cornerstone of resilience, is designed to integrate physical, economic, health, social, and organisational effects of climate change in urban environments. MethodsThis research presents a method for the development of a quantitative spatial and temporal composite measure to assess climate change-related health effects in urban environments. This approach uses inputs such as total population density and densities of various demographics, burden of diseases conditions, flood inundation mapping, and land use change for both historical and current conditions. The research has shown that the methodology presented generates sufficiently accurate information to be useful for planning adaptive strategies. To assemble all inputs into a single measure of health impacts, a weighting system was assigned to apply various priorities to the spatiotemporal data sources. Weights could be varied to assess how they impact the final results. Finally, using spatiotemporal extrapolation methods the future behaviour of the same key spatial variables can be projected. Although this method was developed for application to any coastal mega-city, this thesis demonstrates the results obtained for Metro Vancouver, British Columbia, Canada. FindingsThe data was collected for the years 1981, 1986, 1991, 1996, 2001, 2006, and 2011, because information was readily available for these years. Fine resolution spatial data for these years was used to give a dynamic simulation of possible health impacts for future projections. Linear and auto-regressive spatiotemporal extrapolations were used for projecting a 2050's Metro Vancouver health impact map (HIM). InterpretationThe approach would be useful in the development of more targeted adaptation and risk reduction strategies at a local level. In addition, this methodology can be used to generate inputs for further resilience simulations. The overall value of this approach is that it allows for a more integrated assessment of the city vulnerability and could lead to more effective adaptive strategies. FundingInternational Development Research Center (IDRC), Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), and Social Sciences and Humanities Research Council of Canada (SSHRC).

Subjective spatiotemporal matrix as a new measure of sound field distribution in a room

A new approach for representing the acoustic quality of classroom is presented in this paper. The subjective spatiotemporal measure was developed from a 3D scanning plane by using a dedicated scanning gear to measure the subjective volumetric sound field of a listener inside the room. Calculated coherence matrix is derived from spectral comparison on the appropriate scanning planes. It then could be used for indicating the subjective perception of a listener which is may differ to another listener at adifferent position inside the rooms.

Causal Inference for Cross-Modal Action Selection: A Computational Study in a Decision Making Framework

Animals try to make sense of sensory information from multiple modalities by categorizing them into perceptions of individual or multiple external objects or internal concepts. For example, the brain constructs sensory, spatial representations of the locations of visual and auditory stimuli in the visual and auditory cortices based on retinal and cochlear stimulations. Currently, it is not known how the brain compares the temporal and spatial features of these sensory representations to decide whether they originate from the same or separate sources in space. Here, we propose a computational model of how the brain might solve such a task. We reduce the visual and auditory information to time-varying, finite-dimensional signals. We introduce controlled, leaky integrators as working memory that retains the sensory information for the limited time-course of task implementation. We propose our model within an evidence-based, decision-making framework, where the alternative plan units are saliency maps of space. A spatiotemporal similarity measure, computed directly from the unimodal signals, is suggested as the criterion to infer common or separate causes. We provide simulations that (1) validate our model against behavioral, experimental results in tasks where the participants were asked to report common or separate causes for cross-modal stimuli presented with arbitrary spatial and temporal disparities. (2) Predict the behavior in novel experiments where stimuli have different combinations of spatial, temporal, and reliability features. (3) Illustrate the dynamics of the proposed internal system. These results confirm our spatiotemporal similarity measure as a viable criterion for causal inference, and our decision-making framework as a viable mechanism for target selection, which may be used by the brain in cross-modal situations. Further, we suggest that a similar approach can be extended to other cognitive problems where working memory is a limiting factor, such as target selection among higher numbers of stimuli and selections among other modality combinations.

Robust spatiotemporal stereo against image motion and temporal disparity variation

When there exists camera motion as well as scene motion, the position and disparity of a pixel in an image sequence temporally vary with time. Such image motion (IM) and temporal disparity variation (TDV) degrade the performance of spatiotemporal stereo matching. In this Letter, a robust spatiotemporal similarity measure that addresses IM and TDV is proposed. To this end, an irregular spatiotemporal window whose temporal windows are located by a TDV value and optical flows is designed. In addition, a spatiotemporal guided filter-based aggregation technique using temporal weights based on temporal proximity and flow reliability is presented. To handle a large number of labels effectively, a search range reduction method for finding a probable label set is presented. Experimental results show that the proposed method yields consistent and accurate disparity maps under IM and TDV.

A Measurement Method for Rill and Ephemeral Gully Erosion Assessments

Core Ideas Photogrammetric techniques for spatiotemporal measure of topographic data Physical data for validation and development of soil erosion modeling technology Automated analysis presentation package Rill and ephemeral gully monitoring at high spatial and temporal resolution When flowing water concentrates on hillslopes, the erosivity of the water may only be limited by the erodibility of the soil. Over time, concentrated flow paths may become permanent drainage channels, and such rills and ephemeral gullies often have negative impacts on crop yield and downstream sedimentation. Spatiotemporal topographic assessments of rill and gully dimensions compliment hydraulic erosion estimates, and they can elucidate soil erosion processes and provide data for model validation. Accurate and detailed topographic assessments, however, can be cost prohibitive. The objectives of this study are to describe and evaluate a topographic assessment method with relatively high spatial and temporal resolution, to discuss its costs and limitations, and to provide an assessment procedure for erosion characterization and data optimization. Three locations are evaluated that are pertinent to soil erosion research on the field, plot, and laboratory scale. In each setting, the sites are monumented and monitored using photogrammetric techniques. Photogrammetry is a simple, robust means to track landscape evolution and morphodynamic changes in rills and ephemeral gullies. The assessment procedure describes study site attributes at a variety of spatial and temporal scales, it is cost‐effective, workforce empowering, and reliable, and the analysis and presentation can be automated. Capturing this type of information is critical to an improved understanding of the fundamental principles necessary to enhance modeling technology to estimate erosion potential at various scales and to assess the efficacy of conservation practices.

ClusPath: a temporal-driven clustering to infer typical evolution paths

We propose ClusPath, a novel algorithm for detecting general evolution tendencies in a population of entities. We show how abstract notions, such as the Swedish socio-economical model (in a political dataset) or the companies fiscal optimization (in an economical dataset) can be inferred from low-level descriptive features. Such high-level regularities in the evolution of entities are detected by combining spatial and temporal features into a spatio-temporal dissimilarity measure and using semi-supervised clustering techniques. The relations between the evolution phases are modeled using a graph structure, inferred simultaneously with the partition, by using a "slow changing world" assumption. The idea is to ensure a smooth passage for entities along their evolution paths, which catches the long-term trends in the dataset. Additionally, we also provide a method, based on an evolutionary algorithm, to tune the parameters of ClusPath to new, unseen datasets. This method assesses the fitness of a solution using four opposed quality measures and proposes a balanced compromise.