Representativeness of Taxi GPS-Enabled Travel Time Data Using Gamma Generalized Linear Model

2021 ◽  
Vol 13 (3) ◽  
pp. 36-53
Author(s):  
Glykeria Myrovali ◽  
Theodoros Karakasidis ◽  
Maria Morfoulaki ◽  
Georgia Ayfantopoulou
Keyword(s):  
Linear Model ◽  
Generalized Linear Model ◽  
Information Provision ◽  
Traffic Monitoring ◽  
Time Data ◽  
Time Period ◽  
Travel Time Data ◽  
Rapid Changes ◽  
Strong Relation

The sensor-era has brought rapid changes in transportation; the abundance of data has started changing the traditional way in which planners and engineers approach mobility. Nowadays, traffic monitoring and information provision systems heavily rely on floating car data usually of special vehicles (e.g., trucks, taxi), and the question that arises is whether such sources can provide reliable data for the whole traffic in a complex urban environment. The current paper, through Thessaloniki's (GR) case study, seeks to evaluate the reliability of taxi data compared to the overall traffic. The analysis reveals that for the examined critical urban road paths, there is a strong relation among floating taxi data with the overall traffic that is additionally influenced by other significant factors (e.g., number of lanes, day, time period). Furthermore, a modelling approach with a generalized linear model (gamma with log link) seems appropriate when dealing with skewed and heteroscedastic traffic data.

scholarly journals Application of Google-based Data for Travel Time Analysis: Kaunas City Case Study

2017 ◽  
Vol 29 (6) ◽  
pp. 613-621 ◽  
Author(s):  
Vytautas Dumbliauskas ◽  
Vytautas Grigonis ◽  
Andrius Barauskas
Keyword(s):  
Travel Time ◽  
Time Variability ◽  
Time Data ◽  
Gis Tools ◽  
Travel Time Data ◽  
Challenges And Opportunities ◽  
Time Fluctuation ◽  
Python Programming ◽  
Car Travel

Recently, new traffic data sources have emerged raising new challenges and opportunities when applying novel methodologies. The purpose of this research is to analyse car travel time data collected from smartphones by Google Company. Geographic information system (GIS) tools and Python programming language were employed in this study to establish the initial framework as well as to automatically extract, analyse, and visualize data. The analysis resulted in the calculation of travel time fluctuation during the day, calculation of travel time variability and estimation of origin-destination (OD) skim matrices. Furthermore, we accomplished the accessibility analysis and provided recommendations for further research.

scholarly journals The reasons women choose and stay in a geology major: a qualitative multi-case analysis

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Ron E. Gray ◽  
Alexis T. Riche ◽  
Isabel J. Shinnick-Gordon ◽  
James C. Sample
Keyword(s):  
Role Models ◽  
Critical Incident ◽  
Earth Science ◽  
Time Period ◽  
The Usa ◽  
Data Source ◽  
Introductory Classes ◽  
Iterative Coding ◽  
As Relationship

AbstractDespite earning half of all science and engineering undergraduate degrees between 2007 and 2016 in the USA, women were awarded only 39% of earth science degrees in the same time period. In order to better understand why women are both choosing and staying in geology programs, we conducted a multi-case study of nine current female undergraduate geology majors at a large public university in the USA within a department that is at gender parity among its undergraduate majors. The main data source was audio-recorded critical incident interviews of each participant. Data from the interviews were analyzed through an iterative coding process using codes adapted from previous studies that focused on factors both internal and external to the department. The students said that personal interests, influence by others outside of the department, and introductory classes attracted them to the geology program, but once declared, departmental factors such as relationship with faculty caused them to stay. We also found an emphasis on female role models, especially those teaching introductory courses. We believe this study offers important insights into the ways in which factors leading to recruitment and retention play out in the lived experiences of female geology majors.

scholarly journals Constructing Damage Indices Based on Publicly Available Spatial Data: Exemplified by Earthquakes and Volcanic Eruptions in Indonesia

2021 ◽  
Author(s):  
Emmanuel Skoufias ◽  
Eric Strobl ◽  
Thomas Tveit
Keyword(s):  
Spatial Data ◽  
Volcanic Ash ◽  
Satellite Images ◽  
Fragility Curves ◽  
Volcanic Eruptions ◽  
Damage Indices ◽  
Damage Indicator ◽  
Time Period ◽  
Peak Ground Motion

AbstractThis article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events. For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator. For volcanoes we employ volcanic ash data as a proxy for local damages. Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images. We demonstrate the use of these indices with a case study of Indonesia, a country frequently exposed to earthquakes and volcanic eruptions. The results show that the indices capture the areas with the highest damage, and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014. The indices were constructed using a combination of software programs—ArcGIS/Python, Matlab, and Stata. We also outline what potential freeware alternatives exist. Finally, for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.

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