Spatio-temporal analysis of house price convergence based on a demographical distance

Convergences of house prices have been studied for over three decades, but yet have been confirmed because of spatial heterogeneity and autocorrelations in house prices. A spatio-temporal approach was recently proposed to address the spatial and temporal issues related to house prices. However, most previous studies placed the focus on the spatial heterogeneity and autocorrelations from geographical locations, which neglected other spatial factors. In order to overcome this shortfall, this research argued a demographical distance, constructed by demographical structure and housing market scales, to investigate the house price convergences in Australian capital cities. The results confirmed the house price levels in Canberra, Brisbane and Perth converged to the house price level in Sydney.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. © 2010 World Scientific Publishing Company.

Predicting spatio-temporal distribution for eastern Australian birds using birds Australia's atlas data : survey method, habitat and seasonal effects

Faunal atlases are landscape-level survey collections that can be used for describing spatial and temporal patterns of distribution and densities. They can also serve as a basis for quantitative analysis of factors that may influence the distributions of species. We used a subset of Birds Australia’s Atlas of Australian Birds data (January 1998 to December 2002) to examine the spatio-temporal distribution patterns of 280 selected species in eastern Australia (17–37°S and 136–152°E). Using geographical information systems, this dataset was converted into point coverage and overlaid with a vegetation polygon layer and a half-degree grid. The exploratory data analysis involved calculating species-specific reporting rates spatially, per grid and per vegetation unit, and also temporally, by month and year. We found high spatio-temporal variability in the sampling effort. Using generalised linear models on unaggregated point data, the influences of four factors – survey method and month, geographical location and habitat type – were analysed for each species. When counts of point data were attributed to grid-cells, the total number of species correlated with the total number of surveys, while the number of records per species was highly variable. Surveys had high interannual location fidelity. The predictive values of each of the four factors were species-dependent. Location and habitat were correlated and highly predictive for species with restricted distribution and strong habitat preference. Month was only of importance for migratory species. The proportion of incidental sightings was important for extremely common or extremely rare species. In conclusion, behaviour of species differed sufficiently to require building a customized model for each species to predict distribution. Simple models were effective for habitat specialists with restricted ranges, but for generalists with wide distributions even complex models gave poor predictions.

Big data analytics and visualization with spatio-temporal correlations for traffic accidents

Big data analytics for traffic accidents is a hot topic and has significant values for a smart and safe traffic in the city. Based on the massive traffic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur consequentially by whom. Firstly, we analyze and visualize accident occurrences in both temporal and spatial view. Second, we illustrate spatio-temporal visualization results through two case studies in multiple road segments, and the impact of weather on crash types. These findings of accident occurrences analysis and visualization would not only help traffic police department implement instant personnel assignments among simultaneous accidents, but also inform individual drivers about accident-prone sections and the time span which requires their most attention.

Spatio-temporal selectivity of loss of colour and luminance contrast sensitivity with mutiple sclerosis and optic neuritis

Colour and luminance-contrast thresholds were measured in the presence of dynamic Random Luminance-contrast Masking (RLM) in individuals who had had past diagnoses of optic neuritis (ON) some of whom have progressed to a diagnosis of multiple sclerosis (MS). To explore the spatio-temporal selectivity of chromatic and luminance losses in MS/ON, thresholds were measured using three different sizes and modulation rates of the RLM displays: small checks modulating slowly, medium-sized checks with moderate modulation and large checks modulating rapidly. The colour of the chromatic stimuli used were specified in a cone-excitation space to measure relative impairments in red–green and blue–yellow chromatic channels. These observers showed chromatic thresholds along the L/(L + M) axis that were higher than those along the S-cone axis for all display sizes/modulation rates and both red-green and blue-yellow colour thresholds were higher than luminance-contrast thresholds. The principal change in thresholds with spatio-temporal changes in the display was a reduction in thresholds for L/(L + M) and S-cones with increasing check size and modulation rate. However, luminance contrast thresholds did not change with display size/rate. These results are consistent with MS/ON selectively affecting processing in colour pathways rather than in the magnocellular pathway, and that within the colour pathways neurones with opposed L- and M-cone inputs are more damaged than colour-opponent neurons with input from S-cones.

Physical theory of organisation and consequent neural model of spatio-temporal pattern acquisition

A neurone model (the FORMON) is proposed which provides a mathematical explanation for a range of psychological phenomena and has potential in Artificial Intelligence applications. A general definition of organisation in terms of entropy and information is formulated. The concept of microcodes is introduced to describe the physical nature of organisation. Spatio-temporal pattern acquisition and processing functions attributable to individual neurones are reviewed. The criterion for self-organisation in a neurone is determined as the maximisation of mutual organisation. A feedback control system is proposed to satisfy this criterion and provide an integrated long-term memory of spatio-temporal pattern. This pattern acquisition system is shown to be applicable to dendritic pattern recognition and axonal pattern generation. Provision is also made for adaptation, short-term memory and operant learning. An electro-chemical model of transmission and processing of neural signals is outlined to provide the pattern acquisition functions of the Formon model. A transverse magnetic mode of electrotonic propagation is postulated in addition to the transverse electromagnetic mode. Configurations of the Formon are categorised in terms of possible pattern processing functions. Connective architectures are proposed as self-organising models of acquisitive semantic and syntactic networks.

Layered dynamic probabilistic networks for spatio-temporal modelling

In applications such as tracking and surveillance in large spatial environments, there is a need for representing dynamic and noisy data and at the same time dealing with them at different levels of detail. In the spatial domain, there has been work dealing with these two issues separately, however, there is no existing common framework for dealing with both of them. In this paper, we propose a new representation framework called the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN), capable of handling uncertainty and representing spatial data at various levels of detail. The framework is thus particularly suited to applications in wide-area environments which are characterised by large region size, complex spatial layout and multiple sensors/cameras. For example, a building has three levels: entry/exit to the building, entry/exit between rooms and moving within rooms. To avoid the problem of a relatively large state space associated with a large spatial environment, the LDPN explicitly encodes the hierarchy of connected spatial locations, making it scalable to the size of the environment being modelled. There are three main advantages of the LDPN. First, the reduction in state space makes it suitable for dealing with wide area surveillance involving multiple sensors. Second, it offers a hierarchy of intervals for indexing temporal data. Lastly, the explicit representation of intermediate sub-goals allows for the extension of the framework to easily represent group interactions by allowing coupling between sub-goal layers of different individuals or objects. We describe an adaptation of the likelihood sampling inference scheme for the LDPN, and illustrate its use in a hypothetical surveillance scenario.

Large-scale sampling reveals the spatio-temporal distributions of the jellyfish Aurelia aurita and Cyanea capillata in the Irish Sea

At-sea distributions of large scyphozoan jellyfish across the Irish Sea were studied using visual surface counts from ships of opportunity. Thirty-seven surveys were conducted along two >100 km long transects between Ireland and the UK from April to September in 2009 and 2010. Five species were recorded but only Aurelia aurita and Cyanea capillata were frequently observed. The first formal description of the seasonal changes in the abundances and distributions of these two species in the study area is provided. The highest densities of these species were more likely to be found ~30 km offshore, but large aggregations were present both in coastal and offshore waters. Evidence for aggregations of medusae along physical discontinuities was provided by coupling jellyfish observations with simultaneous records of environmental parameters. The value of surveys from ships of opportunity as cost-effective semi-quantitative tools, to develop local knowledge on jellyfish abundance, distribution, and phenology is discussed.

Spatio-temporal patterns in the Diel Vertical Migration of the Copepod Metridia lucens in the Northeast Atlantic derived from the Continuous Plankton Recorder Survey

The archived data set collected over a 45-yr period (1948-1992) by Continuous Plankton Recorders (CPRs) towed in near-surface waters was used to investigate the diel vertical migration of the copepod Metridia lucens in the northeast Atlantic (47-63?N and 10-30?W). Although the CPR sampling intensity was uniform during the day and the night, M. lucens was caught predominantly in samples collected at night, consistent with a normal diel vertical migration pattern involving movement from greater depth during the day to shallower depths at night. The length of time spent near the surface varied seasonally and was closely correlated (r2 = 0.80) with seasonal change in length of night. The residual variation in length of time spent at the surface was nonrandom, with more time being spent at the surface in spring before the onset of the spring bloom, and less time being spent at the surface in autumn, than that predicted from the length of night at these periods. The timing of this enhanced near-surface occupation in spring varied with latitude, occurring a mean of 3.4 d later per degree of latitude.

Assessing spatio-temporal hydrologic variability: a case-study in western Victoria

This research explored spatial and temporal variability in the relationships between land cover, topography, and climate on streamflows and wetland extents in western Victoria.

Temporal analysis of tourism research collaboration network

Network analysis is an effective tool for the study of collaboration relationships among researchers. Collaboration networks constructed from previous studies, and their changes over time have been studied. However, the impact of individual researchers in collaboration networks has not been investigated systematically. We introduce a new method of measuring the contribution of researchers to the connectivity of collaboration networks and evaluate the importance of researchers by considering both contribution and productivity. Betweenness centrality is found to be better than degree centrality in terms of reflecting the changes of importance of researchers. Accordingly, a method is further proposed to identify key researchers at certain periods. The performance of the identified researchers demonstrates the effectiveness of the proposed method.

Where and when does a ring start and end? Testing the ring-species hypothesis in a species complex of Australian parrots

Speciation, despite ongoing gene flow can be studied directly in nature in ring species that comprise two reproductively isolated populations connected by a chain or ring of intergrading populations. We applied three tiers of spatio-temporal analysis (phylogeny/historical biogeography, phylogeography and landscape/population genetics) to the data from mitochondrial and nuclear genomes of eastern Australian parrots of the Crimson Rosella Platycercus elegans complex to understand the history and present genetic structure of the ring they have long been considered to form. A ring speciation hypothesis does not explain the patterns we have observed in our data (e.g. multiple genetic discontinuities, discordance in genotypic and phenotypic assignments where terminal differentiates meet). However, we cannot reject that a continuous circular distribution has been involved in the group's history or indeed that one was formed through secondary contact at the 'ring's' east and west; however, we reject a simple ring-species hypothesis as traditionally applied, with secondary contact only at its east. We discuss alternative models involving historical allopatry of populations. We suggest that population expansion shown by population genetics parameters in one of these isolates was accompanied by geographical range expansion, secondary contact and hybridization on the eastern and western sides of the ring. Pleistocene landscape and sea-level and habitat changes then established the birds' current distributions and range disjunctions. Populations now show idiosyncratic patterns of selection and drift. We suggest that selection and drift now drive evolution in different populations within what has been considered the ring.

Spatial and temporal distribution of solute leaching in heterogeneous soils: analysis and application to multisampler lysimeter data

Accurate assessment of the fate of salts, nutrients, and pollutants in natural, heterogeneous soils requires a proper quantification of both spatial and temporal solute spreading during solute movement. The number of experiments with multisampler devices that measure solute leaching as a function of space and time is increasing. The breakthrough curve (BTC) can characterize the temporal aspect of solute leaching, and recently the spatial solute distribution curve (SSDC) was introduced to describe the spatial solute distribution. We combined and extended both concepts to develop a tool for the comprehensive analysis of the full spatio-temporal behavior of solute leaching. The sampling locations are ranked in order of descending amount of total leaching (defined as the cumulative leaching from an individual compartment at the end of the experiment), thus collapsing both spatial axes of the sampling plane into one. The leaching process can then be described by a curved surface that is a function of the single spatial coordinate and time. This leaching surface is scaled to integrate to unity, and termed S can efficiently represent data from multisampler solute transport experiments or simulation results from multidimensional solute transport models. The mathematical relationships between the scaled leaching surface S, the BTC, and the SSDC are established. Any desired characteristic of the leaching process can be derived from S. The analysis was applied to a chloride leaching experiment on a lysimeter with 300 drainage compartments of 25 cm2 each. The sandy soil monolith in the lysimeter exhibited fingered flow in the water-repellent top layer. The observed S demonstrated the absence of a sharp separation between fingers and dry areas, owing to diverging flow in the wettable soil below the fingers. Times-to-peak, maximum solute fluxes, and total leaching varied more in high-leaching than in low-leaching compartments. This suggests a stochastic–convective transport process in the high-flow streamtubes, while convection–dispersion is predominant in the low-flow areas. S can be viewed as a bivariate probability density function. Its marginal distributions are the BTC of all sampling locations combined, and the SSDC of cumulative solute leaching at the end of the experiment. The observed S cannot be represented by assuming complete independence between its marginal distributions, indicating that S contains information about the leaching process that cannot be derived from the combination of the BTC and the SSDC.