scholarly journals VISUALIZATION OF SPATIO-TEMPORAL RELATIONS IN MOVEMENT EVENT USING MULTI-VIEW

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1469-1476
Author(s):  
K. Zheng ◽  
D. Gu ◽  
F. Fang ◽  
Y. Wang ◽  
H. Liu ◽  
...  
Keyword(s):  
Knowledge Discovery ◽  
Multiple Scales ◽  
Temporal Relations ◽  
Discovery Process ◽  
Trajectory Data ◽  
Statistical Tools ◽  
Multi Scale ◽  
Spatio Temporal ◽  
Visual Interface ◽  
Taxi Trajectory

Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

scholarly journals Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

2020 ◽  
Vol 13 (1) ◽  
pp. 112
Author(s):  
Helai Huang ◽  
Jialing Wu ◽  
Fang Liu ◽  
Yiwei Wang
Keyword(s):  
Waiting Time ◽  
Urban Areas ◽  
Transportation Systems ◽  
Trajectory Data ◽  
Peak Period ◽  
Important Indicator ◽  
Destination Attractiveness ◽  
Urban Accessibility ◽  
Spatio Temporal ◽  
Taxi Trajectory

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility.

scholarly journals Multi-scale event synchronization analysis for unravelling climate processes: A wavelet-based approach

2017 ◽  
Author(s):  
Ankit Agarwal ◽  
Norbert Marwan ◽  
Maheswaran Rathinasamy ◽  
Bruno Merz ◽  
Jürgen Kurths
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Time Scale ◽  
Temporal Dynamics ◽  
Multiple Scales ◽  
Nonlinear Interactions ◽  
Reference Time ◽  
Multi Scale ◽  
Spatio Temporal ◽  
Different Time Scales

Abstract. The temporal dynamics of climate processes are spread across different time scales and, as such, the study of these processes only at one selected time scale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. For capturing the nonlinear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analyse the time series at one reference time scale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, wavelet based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various time scales. The proposed method allows the study of spatio-temporal patterns across different time scales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different time scales.

Detecting Taxi Trajectory Anomaly Based on Spatio-Temporal Relations

2021 ◽  
pp. 1-12
Author(s):  
Shiyou Qian ◽  
Bin Cheng ◽  
Jian Cao ◽  
Guangtao Xue ◽  
Yanmin Zhu ◽  
...  
Keyword(s):  
Temporal Relations ◽  
Spatio Temporal ◽  
Taxi Trajectory

scholarly journals Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach

2017 ◽  
Vol 24 (4) ◽  
pp. 599-611 ◽  
Author(s):  
Ankit Agarwal ◽  
Norbert Marwan ◽  
Maheswaran Rathinasamy ◽  
Bruno Merz ◽  
Jürgen Kurths
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Real World ◽  
Temporal Dynamics ◽  
Multiple Scales ◽  
Temporal Patterns ◽  
Multi Scale ◽  
Main Drawback ◽  
Spatio Temporal ◽  
Linear Interactions

Abstract. The temporal dynamics of climate processes are spread across different timescales and, as such, the study of these processes at only one selected timescale might not reveal the complete mechanisms and interactions within and between the (sub-)processes. To capture the non-linear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analysing the time series at one reference timescale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, the wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various timescales. The proposed method allows the study of spatio-temporal patterns across different timescales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different timescales.

scholarly journals SPATIO-TEMPORAL CHARACTERISTICS OF RESIDENT TRIP BASED ON POI AND OD DATA OF FLOAT CAR IN BEIJING

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 99-105
Author(s):  
N. Mou ◽  
J. Li ◽  
L. Zhang ◽  
W. Liu ◽  
Y. Xu
Keyword(s):  
Research Unit ◽  
Concentric Circle ◽  
Relative Dispersion ◽  
Residential Areas ◽  
Trajectory Data ◽  
Periodic Patterns ◽  
Temporal Characteristics ◽  
The Road ◽  
Spatio Temporal ◽  
Taxi Trajectory

Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method – based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then，combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion – spatial aggregation – spatial relative dispersion" in one day.

scholarly journals A Conceptual Paper on Multi-Scale Applications in Cloud Environment with Reference to Variety of Data

2020 ◽  
Vol 9 (5) ◽  
pp. 1229-1235
Keyword(s):  
Cloud Computing ◽  
Multiple Scales ◽  
Review Literature ◽  
Cloud Environment ◽  
Multi Scale ◽  
Cloud Application ◽  
Conceptual Paper ◽  
Spatio Temporal ◽  
Definition Of ◽  
New Research

Developments in Cloud Computing has opened up new avenues for cutting – edge technology applications. It is the conventional technology that deploys the applications and services on internet servers instead of traditional servers. Software-as-a-Service (SaaS) allows access to a variety of applications on the cloud commonly known as Multi-scale applications. Social and Professional media like Whatsapp, Facebook, Twitter, Instagram, LinkedIn, ResearchGate etc. have migrated to cloud. The terms scale and scalability in cloud environment has been used in different contexts. The applications can be scaled up or down based on the network traffic scenario, and has thus opened up a Pandora’s Box in new research and development of multi–scale cloud based applications. This conceptual paper attempts to review literature across various domains where the term multi-scale, scaling, cloud based application have been used and arrive at a reasonable, crisp, concise yet accurate definition of the term multi – scale and multi–scale cloud application. The term “Multi – Scale” is used in various fields referring to multiple scales applied to arrive at solutions to spatio-temporal problems. This conceptual paper attempts to associate a formal definition to the term “multi-scale cloud application” in the cloud computing world. The proposed definition of the said term is extremely relevant in the context of multi–scale applications developed in recent times.

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