scholarly journals COVID-19 geoviz for spatio-temporal structures detection

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
Jacques Gautier ◽  
Maria-Jesus Lobo ◽  
Benjamin Fau ◽  
Armand Drugeon ◽  
Sidonie Christophe ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Growth Ring ◽  
Temporal Trends ◽  
Space Time ◽  
Event Data ◽  
Web Based ◽  
Temporal Structures ◽  
Visualization Tools ◽  
Spatio Temporal ◽  
Spatial Entities

Abstract. The spread of COVID-19 has motivated a wide interest in visualization tools to represent the pandemic’s spatio-temporal evolution. This tools usually rely on dashboard environments which depict COVID-19 data as temporal series related to different indicators (number of cases, deaths) calculated for several spatial entities at different scales (countries or regions). In these tools, diagrams (line charts or histograms) display the temporal component of data, and 2D cartographic representations display the spatial distribution of data at one moment in time. In this paper, we aim at proposing novel visualization designs in order to help medical experts to detect spatio-temporal structures such as clusters of cases and spatial axes of propagation of the epidemic, through a visual analysis of detailed COVID-19 event data. In this context, we investigate and revisit two visualizations, one based on the Growth Ring Map technique and the other based on the space-time cube applied on a spatial hexagonal grid. We assess the potential of these visualizations for the visual analysis of COVID-19 event data, through two proofs of concept using synthetic cases data and web-based prototypes. The Grow Ring Map visualization appears to facilitate the identification of clusters and propagation axes in the cases distribution, while the space-time cube appears to be suited for the identification of local temporal trends.

scholarly journals Spatio-temporal analysis and visualisation of the anthrax epidemic situation in livestock in Kazakhstan over the period 1933-2016

2017 ◽  
Author(s):  
Sarsenbay K. Abdrakhmanov ◽  
Yersyn Y. Mukhanbetkaliyev ◽  
Fedor I. Korennoy ◽  
Bolat Sh. Karatayev ◽  
Aizada A. Mukhanbetkaliyeva ◽  
...  
Keyword(s):  
Temporal Trends ◽  
Small Ruminants ◽  
Temporal Analysis ◽  
Space Time ◽  
Decision Makers ◽  
Annual Number ◽  
Spatio Temporal ◽  
The Republic ◽  
Increasing Trends ◽  
Historical Periods

An analysis of the anthrax epidemic situation among livestock animals in the Republic of Kazakhstan over the period 1933-2016 is presented. During this time, 4,064 anthrax outbreaks (mainly in cattle, small ruminants, pigs and horses) were recorded. They fall into five historical periods of increase and decrease in the annual anthrax incidence (1933-1953; 1954-1968; 1969-1983; 1984- 2001; and 2002-2016), which has been associated with changes in economic activity and veterinary surveillance. To evaluate the temporal trends of incidence variation for each of these time periods, the following methods were applied: i) spatio-temporal analysis using a space-time cube to assess the presence of hotspots (i.e., areas of outbreak clustering) and the trends of their emergence over time; and ii) a linear regression model that was used to evaluate the annual numbers of outbreaks as a function of time. The results show increasing trends during the first two periods followed by a decreasing trend up to now. The peak years of anthrax outbreaks occurred in 1965-1968 but outbreaks still continue with an average annual number of outbreaks of 1.2 (95% confidence interval: 0.6-1.8). The space-time analysis approach enabled visualisation of areas with statistically significant increasing or decreasing trends of outbreak clustering providing a practical opportunity to inform decision-makers and allowing the veterinary services to concentrate their efforts on monitoring the possible risk factors in the identified locations.

scholarly journals RESEARCH ON VISUAL ANALYSIS METHODS OF TERRORISM EVENTS

2016 ◽  
Vol XLI-B2 ◽  
pp. 191-196
Author(s):  
Wenyue Guo ◽  
Haiyan Liu ◽  
Anzhu Yu ◽  
Jing Li
Keyword(s):  
Visual Analysis ◽  
Temporal Distribution ◽  
Development Trend ◽  
Event Data ◽  
Thematic Map ◽  
The World ◽  
Spatio Temporal ◽  
Global Terrorism Database ◽  
The Development Trend ◽  
Security Incidents

Under the situation that terrorism events occur more and more frequency throughout the world, improving the response capability of social security incidents has become an important aspect to test governments govern ability. Visual analysis has become an important method of event analysing for its advantage of intuitive and effective. To analyse events’ spatio-temporal distribution characteristics, correlations among event items and the development trend, terrorism event’s spatio-temporal characteristics are discussed. Suitable event data table structure based on “5W” theory is designed. Then, six types of visual analysis are purposed, and how to use thematic map and statistical charts to realize visual analysis on terrorism events is studied. Finally, experiments have been carried out by using the data provided by Global Terrorism Database, and the results of experiments proves the availability of the methods.

scholarly journals RESEARCH ON VISUAL ANALYSIS METHODS OF TERRORISM EVENTS

2016 ◽  
Vol XLI-B2 ◽  
pp. 191-196
Author(s):  
Wenyue Guo ◽  
Haiyan Liu ◽  
Anzhu Yu ◽  
Jing Li
Keyword(s):  
Visual Analysis ◽  
Temporal Distribution ◽  
Development Trend ◽  
Event Data ◽  
Thematic Map ◽  
The World ◽  
Spatio Temporal ◽  
Global Terrorism Database ◽  
The Development Trend ◽  
Security Incidents

Under the situation that terrorism events occur more and more frequency throughout the world, improving the response capability of social security incidents has become an important aspect to test governments govern ability. Visual analysis has become an important method of event analysing for its advantage of intuitive and effective. To analyse events’ spatio-temporal distribution characteristics, correlations among event items and the development trend, terrorism event’s spatio-temporal characteristics are discussed. Suitable event data table structure based on “5W” theory is designed. Then, six types of visual analysis are purposed, and how to use thematic map and statistical charts to realize visual analysis on terrorism events is studied. Finally, experiments have been carried out by using the data provided by Global Terrorism Database, and the results of experiments proves the availability of the methods.

Geovisualization and harmonic analysis for the exploratory search of localized cyclic recurrences in spatio-temporal event data

GEOMATICA ◽  
2020 ◽  
pp. 1-23
Author(s):  
Jacques Gautier ◽  
Paule-Annick Davoine ◽  
Claire Cunty
Keyword(s):  
Visual Search ◽  
Harmonic Analysis ◽  
Ad Hoc ◽  
Visual Analysis ◽  
Spatial Clustering ◽  
Exploratory Analysis ◽  
Temporal Data ◽  
Event Data ◽  
Visual Approach ◽  
Spatio Temporal

Many geovisualization environments integrate graphical representations of time. Some of them include representation of both linear and cyclic aspects of time, providing an exploratory analysis of spatio-temporal data through several temporal cyclic scales. However, few of them provide an exploratory analysis of localized cyclic recurrences in spatio-temporal data. Ad hoc temporal diagrams, representing both linear and cyclic aspects of time, provide a visual search for cyclic recurrences in temporal data when the possibility is left to the user to perform a gradual modification of the represented cyclic scale’s duration. The combination of these graphic representations of time, with cartographic representations, displaying the spatial distribution of such cyclic recurrences, could provide an exploratory analysis of localized cyclic recurrences in spatio-temporal data. Mathematical tools coming from other scientific fields, such as the harmonic analysis, offer another way to identify cyclic behaviors in temporal data. Combining the visual approach offered by specifically designed geovisualization environments, with a harmonic analysis that suggests searching paths to the user during its exploratory analysis, can then improve the visual search for localized cyclic recurrences. We propose a geovisualization environment, which combines, on one hand, a visual analysis of localized cyclic recurrences in spatio-temporal data, using ad hoc temporal diagrams, cartographic representations, and specific semiologic rules, and on the other hand, mathematical tools, such as harmonic analysis and spatial clustering, that provide searching paths to the user for its visual analysis. This approach is supported by a geovisualization environment, GrAPHiST, which provides an exploratory analysis of spatio-temporal event data.

eMap: A Web Application for Identifying and Visualizing Electron or Hole Hopping Pathways in Proteins

2019 ◽  
Author(s):  
Ruslan N. Tazhigulov ◽  
James R. Gayvert ◽  
Melissa Wei ◽  
Ksenia B. Bravaya
Keyword(s):  
Web Application ◽  
Shortest Paths ◽  
Coarse Grained ◽  
Decay Parameter ◽  
Electron Hole ◽  
Web Based ◽  
Aromatic Amino Acid Residue ◽  
Pathways Model ◽  
Visualization Tools ◽  
Effective Decay

<p>eMap is a web-based platform for identifying and visualizing electron or hole transfer pathways in proteins based on their crystal structures. The underlying model can be viewed as a coarse-grained version of the Pathways model, where each tunneling step between hopping sites represented by electron transfer active (ETA) moieties is described with one effective decay parameter that describes protein-mediated tunneling. ETA moieties include aromatic amino acid residue side chains and aromatic fragments of cofactors that are automatically detected, and, in addition, electron/hole residing sites that can be specified by the users. The software searches for the shortest paths connecting the user-specified electron/hole source to either all surface-exposed ETA residues or to the user-specified target. The identified pathways are ranked based on their length. The pathways are visualized in 2D as a graph, in which each node represents an ETA site, and in 3D using available protein visualization tools. Here, we present the capability and user interface of eMap 1.0, which is available at https://emap.bu.edu.</p>

scholarly journals Spatio-Temporal Visual Analysis for Urban Traffic Characters Based on Video Surveillance Camera Data

2021 ◽  
Vol 10 (3) ◽  
pp. 177
Author(s):  
Haochen Zou ◽  
Keyan Cao ◽  
Chong Jiang
Keyword(s):  
Video Surveillance ◽  
Traffic Management ◽  
Visual Analysis ◽  
Urban Traffic ◽  
License Plate ◽  
Road Vehicle ◽  
Urban Road ◽  
Surveillance Camera ◽  
Vehicle Density ◽  
Spatio Temporal

Urban road traffic spatio-temporal characters reflect how citizens move and how goods are transported, which is crucial for trip planning, traffic management, and urban design. Video surveillance camera plays an important role in intelligent transport systems (ITS) for recognizing license plate numbers. This paper proposes a spatio-temporal visualization method to discover urban road vehicle density, city-wide regional vehicle density, and hot routes using license plate number data recorded by video surveillance cameras. To improve the accuracy of the visualization effect, during data analysis and processing, this paper utilized Internet crawler technology and adopted an outlier detection algorithm based on the Dixon detection method. In the design of the visualization map, this paper established an urban road vehicle traffic index to intuitively and quantitatively reveal the traffic operation situation of the area. To verify the feasibility of the method, an experiment in Guiyang on data from road video surveillance camera system was conducted. Multiple urban traffic spatial and temporal characters are recognized concisely and efficiently from three visualization maps. The results show the satisfactory performance of the proposed framework in terms of visual analysis, which will facilitate traffic management and operation.

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