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Author: David J. Maguire Publisher: Esri Press ISBN: Category : Computers Languages : en Pages : 510
Book Description
A guide for geographic analysts, modelers, software engineers, and GIS professionals, this book discusses agent-based modeling, dynamic feedback and simulation modeling, as well as links between models and GIS software. This collection also presents a state-of-the-art understanding of applications based on environmental, atmospheric, hydrological, urban, social, health, and economic models.
Author: David J. Maguire Publisher: Esri Press ISBN: Category : Computers Languages : en Pages : 510
Book Description
A guide for geographic analysts, modelers, software engineers, and GIS professionals, this book discusses agent-based modeling, dynamic feedback and simulation modeling, as well as links between models and GIS software. This collection also presents a state-of-the-art understanding of applications based on environmental, atmospheric, hydrological, urban, social, health, and economic models.
Author: Andrew Crooks Publisher: SAGE Publications Limited ISBN: 9781473958654 Category : Social Science Languages : en Pages : 0
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.
Author: Philippe Rigaux Publisher: Morgan Kaufmann ISBN: 9781558605886 Category : Computers Languages : en Pages : 444
Book Description
The authors explore and explain current techniques for handling the specialised data that describes geographical phenomena in a study that will be of great value to computer scientists and geographers working with spatial databases.
Author: Elias T. Krainski Publisher: CRC Press ISBN: 0429629850 Category : Mathematics Languages : en Pages : 284
Book Description
Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio-temporal models * Measurement error spatial models * Modeling preferential sampling * Spatial and spatio-temporal models with physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with spatial effects * Penalized Complexity priors for spatial models All the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book. The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.
Author: Robin Lovelace Publisher: CRC Press ISBN: 1351396900 Category : Mathematics Languages : en Pages : 354
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/.
Author: Sara Shirowzhan Publisher: MDPI ISBN: 3039360302 Category : Technology & Engineering Languages : en Pages : 166
Book Description
This book covers a range of topics including selective technologies and algorithms that can potentially contribute to developing an intelligent environment and smarter cities. While the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers, before the project is approved. This book also presents an agenda for future investigations to address the need for advanced tools such as mobile scanners, Geospatial Artificial Intelligence, Unmanned Aerial Vehicles, Geospatial Augmented Reality apps, Light Detection, and Ranging in smart cities. Some of selected specific tools presented in this book are as a simulator for improving the smart parking practices by modelling drivers with activity plans, a bike optimization algorithm to increase the efficiency of bike stations, an agent-based model simulation of human mobility with the use of mobile phone datasets. In addition, this book describes the use of numerical methods to match the network demand and supply of bicycles, investigate the distribution of railways using different indicators, presents a novel algorithm of direction-aware continuous moving K-nearest neighbor queries in road networks, and presents an efficient staged evacuation planning algorithm for multi-exit buildings.
Author: Alias Abdul-Rahman Publisher: Springer Science & Business Media ISBN: 3540741674 Category : Science Languages : en Pages : 291
Book Description
This book covers fundamental aspects of spatial data modelling specifically on the aspect of three-dimensional (3D) modelling and structuring. Realisation of "true" 3D GIS spatial system needs a lot of effort, and the process is taking place in various research centres and universities in some countries. The development of spatial data modelling for 3D objects is the focus of this book.
Author: Claudia Maria Bauzer Medeiros Publisher: EOLSS Publications ISBN: 190583991X Category : Languages : en Pages : 410
Book Description
Advanced Geographic Information Systems is a component of Encyclopedia of Earth and Atmospheric Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The content of the Theme on Advanced Geographic Information Systems is organized with state-oc-the-art presentations covering the following aspects of the subject: Spatio-Temporal Information Systems; Interacting with GIS - From Paper Cartography to Virtual Environments; Spatial Data Management: Topic Overview; Introduction to Spatial Decision Support Systems; GIS Interoperability, from Problems to Solutions. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.
Author: Marta Blangiardo Publisher: John Wiley & Sons ISBN: 1118326555 Category : Mathematics Languages : en Pages : 322
Book Description
Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations
Author: David J. Maguire
Author: David J. Maguire
Author: M. Molenaar
Author: Andrew Crooks
Author: Philippe Rigaux
Author: Elias T. Krainski
Author: Robin Lovelace
Author: Sara Shirowzhan
Author: Alias Abdul-Rahman
Author: Claudia Maria Bauzer Medeiros
Author: Marta Blangiardo