Using geographic information systems to define and map commuting patterns as inputs to agent-based models

Using geographic information systems to define and map commuting patterns as inputs to agent-based models PDF Author: David P. Chrest
Publisher: RTI Press
ISBN:
Category : Computers
Languages : en
Pages : 24

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Book Description
By understanding the movement patterns of people, mathematical modelers can develop models that can better analyze and predict the spread of infectious diseases. People can come into close contact in their workplaces. This report describes methods to develop georeferenced commuting patterns that can be used to characterize the work-related movement of US populations and help agent-based modelers predict workplace contacts that result in disease transmission. We used a census data product called "Census Spatial Tabulation: Census Track of Work by Census Tract of Residence (STP64)" as the data source to develop commuting pattern data for agent-based synthesized populations databases and to develop map products to visualize commuting patterns in the United States. The three primary maps we developed show inbound, outbound, and net change levels of inbound versus outbound commuters by census tract for the year 2000. Net change counts of commuters are visualized as elevations. The results can be used to quantify and assign commuting patterns of synthesized populations among different census tracts.

Using geographic information systems to define and map commuting patterns as inputs to agent-based models

Using geographic information systems to define and map commuting patterns as inputs to agent-based models PDF Author: David P. Chrest
Publisher: RTI Press
ISBN:
Category : Computers
Languages : en
Pages : 24

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Book Description
By understanding the movement patterns of people, mathematical modelers can develop models that can better analyze and predict the spread of infectious diseases. People can come into close contact in their workplaces. This report describes methods to develop georeferenced commuting patterns that can be used to characterize the work-related movement of US populations and help agent-based modelers predict workplace contacts that result in disease transmission. We used a census data product called "Census Spatial Tabulation: Census Track of Work by Census Tract of Residence (STP64)" as the data source to develop commuting pattern data for agent-based synthesized populations databases and to develop map products to visualize commuting patterns in the United States. The three primary maps we developed show inbound, outbound, and net change levels of inbound versus outbound commuters by census tract for the year 2000. Net change counts of commuters are visualized as elevations. The results can be used to quantify and assign commuting patterns of synthesized populations among different census tracts.

Using Geographic Information Systems to Define and Map Commuting Patterns as Inputs to Agent-based Models

Using Geographic Information Systems to Define and Map Commuting Patterns as Inputs to Agent-based Models PDF Author: David P. Chrest
Publisher:
ISBN:
Category : Community-acquired infections
Languages : en
Pages : 20

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Book Description


Agent-Based Models of Geographical Systems

Agent-Based Models of Geographical Systems PDF Author: Alison J. Heppenstall
Publisher: Springer Science & Business Media
ISBN: 9048189276
Category : Social Science
Languages : en
Pages : 747

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Book Description
This unique book brings together a comprehensive set of papers on the background, theory, technical issues and applications of agent-based modelling (ABM) within geographical systems. This collection of papers is an invaluable reference point for the experienced agent-based modeller as well those new to the area. Specific geographical issues such as handling scale and space are dealt with as well as practical advice from leading experts about designing and creating ABMs, handling complexity, visualising and validating model outputs. With contributions from many of the world’s leading research institutions, the latest applied research (micro and macro applications) from around the globe exemplify what can be achieved in geographical context. This book is relevant to researchers, postgraduate and advanced undergraduate students, and professionals in the areas of quantitative geography, spatial analysis, spatial modelling, social simulation modelling and geographical information sciences.

GIS-Based Simulation and Analysis of Intra-Urban Commuting

GIS-Based Simulation and Analysis of Intra-Urban Commuting PDF Author: Yujie Hu
Publisher: CRC Press
ISBN: 0429682417
Category : Mathematics
Languages : en
Pages : 110

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Book Description
Commuting, the daily link between residences and workplaces, sets up the complex interaction between the two most important land uses (residential and employment) in a city, and dictates the configuration of urban structure. In addition to prolonged time and stress for individual commuters on traffic, commuting comes with additional societal costs including elevated crash risks, worsening air quality, and louder traffic noise, etc. These issues are important to city planners, policy researchers, and decision makers. GIS-Based Simulation and Analysis of Intra-Urban Commuting, presents GIS-based simulation, optimization and statistical approaches to measure, map, analyze, and explain commuting patterns including commuting length and efficiency. Several GIS-automated easy-to-use tools will be available, along with sample data, for readers to download and apply to their own studies. This book recognizes that reporting errors from survey data and use of aggregated zonal data are two sources of bias in estimation of wasteful commuting, it studies the temporal trend of intraurban commuting pattern based on the most recent period newly-available 2006-2010, and it focuses on commuting, and especially wasteful commuting within US cities. It includes ready-to-download GIS-based simulation tools and sample data, and an explanation of optimization and statistical techniques of how to measure commuting, as well as presenting a methodology that can be applicable to other studies. This book is an invaluable resource for students, researchers, and practitioners in geography, urban planning, public policy, transportation engineering, and other related disciplines.

Agent-Based Modelling and Geographical Information Systems

Agent-Based Modelling and Geographical Information Systems PDF Author: Andrew Crooks
Publisher: SAGE Publications Limited
ISBN: 9781473958647
Category : Social Science
Languages : en
Pages : 0

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Book Description
This is the era of Big Data and computational social science. It is an era that requires tools which can do more than visualise data but also model the complex relation between data and human action, and interaction. Agent-Based Models (ABM) - computational models which simulate human action and interaction – do just that. This textbook explains how to design and build ABM and how to link the models to Geographical Information Systems. It guides you from the basics through to constructing more complex models which work with data and human behaviour in a spatial context. All of the fundamental concepts are explained and related to practical examples to facilitate learning (with models developed in NetLogo with all code examples available on the accompanying website). You will be able to use these models to develop your own applications and link, where appropriate, to Geographical Information Systems. All of the key ideas and methods are explained in detail: geographical modelling; an introduction to ABM; the fundamentals of Geographical Information Science; why ABM and GIS; using QGIS; designing and building an ABM; calibration and validation; modelling human behavior. An applied primer, that provides fundamental knowledge and practical skills, it will provide you with the skills to build and run your own models, and to begin your own research projects.

Agent-Based Models and Complexity Science in the Age of Geospatial Big Data

Agent-Based Models and Complexity Science in the Age of Geospatial Big Data PDF Author: Liliana Perez
Publisher: Springer
ISBN: 3319659936
Category : Science
Languages : en
Pages : 111

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Book Description
This book contains a selection of papers presented during a special workshop on Complexity Science organized as part of the 9th International Conference on GIScience 2016. Expert researchers in the areas of Agent-Based Modeling, Complexity Theory, Network Theory, Big Data, and emerging methods of Analysis and Visualization for new types of data explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.

Mapping Your Community

Mapping Your Community PDF Author:
Publisher:
ISBN:
Category : Social Science
Languages : en
Pages : 156

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Book Description
Powerful desktop computer systems are now affordable to local groups working to improve conditions in America1s distressed urban neighborhoods. This creates the opportunity for them to use geographic information (data that can be displayed on maps) quickly and easily to help them achieve their neighborhood improvement objectives. This report introduces the new opportunities that exist for using computer based geographic information in their work. Sections: advances in the accessibility of geographic data; using geographic data; neighborhood-level applications; citywide initiatives and policy change; and catalog of data sources. Illustrated.

Spatial Microsimulation: A Reference Guide for Users

Spatial Microsimulation: A Reference Guide for Users PDF Author: Robert Tanton
Publisher: Springer Science & Business Media
ISBN: 9400746237
Category : Social Science
Languages : en
Pages : 272

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Book Description
This book is a practical guide on how to design, create and validate a spatial microsimulation model. These models are becoming more popular as academics and policy makers recognise the value of place in research and policy making. Recent spatial microsimulation models have been used to analyse health and social disadvantage for small areas; and to look at the effect of policy change for small areas. This provides a powerful analysis tool for researchers and policy makers. This book covers preparing the data for spatial microsimulation; a number of methods for both static and dynamic spatial microsimulation models; validation of the models to ensure the outputs are reasonable; and the future of spatial microsimulation. The book will be an essential handbook for any researcher or policy maker looking to design and create a spatial microsimulation model. This book will also be useful to those policy makers who are commissioning a spatial microsimulation model, or looking to commission work using a spatial microsimulation model, as it provides information on the different methods in a non-technical way.

Geocomputation with R

Geocomputation with R PDF Author: Robin Lovelace
Publisher: CRC Press
ISBN: 1351396900
Category : Mathematics
Languages : en
Pages : 335

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Book Description
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.

Toward Integration of Bayesian Networks with Geographic Information Systems and Complex Systems Theory for Urban Land Use Change Modelling

Toward Integration of Bayesian Networks with Geographic Information Systems and Complex Systems Theory for Urban Land Use Change Modelling PDF Author: Verda Kocabas Ersahin
Publisher:
ISBN:
Category : Cellular automata
Languages : en
Pages : 0

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Book Description
Human-initiated land use change is the most significant factor behind the loss of agricultural and forested areas, thus global climate change. It is important to understand the reasons behind land use decisions as it is to understand their consequences. Empirical observations and controlled experimentation are not usually feasible methods for studying this change. Therefore, researchers have employed complex systems theory (or complexity theory) to help them understand and model dynamic land use change process in cities. Cellular automata (CA) theory and agent-based modeling have widely applied in land use change modelling. CA models can easily model spatial process that is changing over time, and can handle fine scale dynamics of these spatial processes. Agent-based models (ABMs) excel at relating the heterogeneous behaviour of agents with different information, different decision rules, and different situation to the macro behaviour of the overall system. While both have advantages, they have a number of challenges when applied to land use change. One of the aims of this dissertation is to develop novel modelling approaches that integrate geographic information systems (GIS), CA and ABMs with Bayesian Networks (BNs) for overcoming limitations in the modelling process by significantly reducing the tedious work in defining parameter values, transition rules and model structures. As the use of land use models in planning is not widely accepted and not trusted fully by the urban planners, the other aim is to link land use models with planning support systems (PSS), especially to use enhanced ABMs in PSS. Therefore, the proposed modelling approaches were applied to assist in understanding the patterns and controls of land use change both spatially and temporarily for the Metro Vancouver region. They were used to analyze the effects of planning decisions in accordance with the sustainable development point of view.