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Geoinformatics for Intelligent Transportation

Overview of attention for book
Cover of 'Geoinformatics for Intelligent Transportation'

Table of Contents

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    Book Overview
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    Chapter 1 Investigation of Sonar Stabilisation Method for Improved Seafloor Image Quality
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    Chapter 2 Global Land Cover Classification Based on Microwave Polarization and Gradient Ratio (MPGR)
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    Chapter 3 Optimal Path Problem with Possibilistic Weights
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    Chapter 4 Optimal Placement of the Bike Rental Stations and Their Capacities in Olomouc
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    Chapter 5 Detecting Spatial and Temporal Route Information of GPS Traces
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    Chapter 6 Impact of Particular Indicators of Urban Development of Cities in the Czech Republic on Average Road Traffic Intensity
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    Chapter 7 Time of Day Dependency of Public Transport Accessibility in the Czech Republic
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    Chapter 8 Automatic Generation of 3D Building Models from Point Clouds
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    Chapter 9 Towards a Solution for the Public Web-Based GIS Monitoring and Alerting System
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    Chapter 10 Demand and Supply of Transport Connections for Commuting in the Czech Republic
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    Chapter 11 Train Platforming Problem
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    Chapter 12 Examples of the Implementation of Fuzzy Models in Tourism in the South Moravian Region
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    Chapter 13 Photovoltaics as an Element of Intelligent Transport System Development
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    Chapter 14 Urban Heartbeats (Daily Cycle of Public Transport Intensity)
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    Chapter 15 Improving Geolocation by Combining GPS with Image Analysis
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    Chapter 16 The Impact of Data Aggregation on Potential Accessibility Values
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    Chapter 17 The Accuracy of Digital Models for Road Design
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    Chapter 18 GPS Data and Car Drivers’ Parking Search Behavior in the City of Turnhout, Belgium
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    Chapter 19 Mobile Application for Acquiring Geodata on Public Transport Network
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Geoinformatics for Intelligent Transportation
Published by
Springer International Publishing, November 2014
DOI 10.1007/978-3-319-11463-7
978-3-31-911462-0, 978-3-31-911463-7

Ivan, Igor, Benenson, Itzhak, Jiang, Bin, Horák, Jiří, Haworth, James, Inspektor, Tomáš

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 10%
Student > Ph. D. Student 2 5%
Lecturer 2 5%
Student > Postgraduate 2 5%
Student > Doctoral Student 1 2%
Other 3 7%
Unknown 27 66%
Readers by discipline Count As %
Engineering 12 29%
Earth and Planetary Sciences 1 2%
Unknown 28 68%