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Spatial Data Analysis

Author : Robert P. Haining
Publisher : Cambridge University Press
Page : 462 pages
File Size : 50,54 MB
Release : 2003-04-17
Category : Business & Economics
ISBN : 9780521774376

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Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy related research. Covering fundamental problems concerning how attributes in geographical space are represented to the latest methods of exploratory spatial data analysis and spatial modeling, it is designed to take the reader through the key areas that underpin the analysis of spatial data, providing a platform from which to view and critically appreciate many of the key areas of the field. Parts of the text are accessible to undergraduate and master's level students, but it also contains sufficient challenging material that it will be of interest to geographers, social and economic scientists, environmental scientists and statisticians, whose research takes them into the area of spatial analysis.

Spatial Analysis Methods and Practice

Author : George Grekousis
Publisher : Cambridge University Press
Page : 535 pages
File Size : 38,95 MB
Release : 2020-06-11
Category : Reference
ISBN : 1108498981

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An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.

Spatial Mathematics

Author : Sandra Lach Arlinghaus
Publisher : CRC Press
Page : 302 pages
File Size : 32,81 MB
Release : 2013-06-26
Category : Mathematics
ISBN : 146650532X

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In terms of statistics, GIS offers many connections. With GIS, data are gathered, displayed, summarized, examined, and interpreted to discover patterns. Spatial Mathematics: Theory and Practice through Mapping uses GIS as a platform to teach mathematical concepts and skills through visualization of numbers. It examines theory and practice from disparate academic disciplines such as geography, mathematics, physics, and general social science. This approach allows students to grapple with biodiversity, crime, natural hazards, climate, energy, water, and other relevant real-world issues of the twenty-first century. Includes QR Codes Linked to Animated Maps, a Mapping Activity Site, or to an Interactive Webpage, Creating an Interactive Resource That Stays Relevant The book integrates competing philosophical views of the world: synthesis and analysis. These two approaches yield different results and employ different tools. This book considers both approaches to looking at real-world issues that have mathematics as a critical, but often unseen, component. This approach shows readers how to use mathematics to consider the broad problem at hand and to explore diverse realms in the worlds of geography and mathematics and in their interface. A truly interdisciplinary text, the book bridges the worlds of mathematics and geography and demonstrates how they are inextricably linked. It takes advantage of the convergence in citizen science, STEM education, and mapping that help readers become critical consumers of data—understanding its content, quality, limitations, and benefits. It provides thorough grounding in the analytical, statistical, and computational skills required for working in any field that uses geospatial technologies—not just surveyors and remote sensing analysts.

Geospatial Health Data

Author : Paula Moraga
Publisher : CRC Press
Page : 217 pages
File Size : 34,15 MB
Release : 2019-11-26
Category : Medical
ISBN : 1000732150

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Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.

Spatial Analysis

Author : Lorenzo Jade
Publisher : Larsen and Keller Education
Page : 212 pages
File Size : 40,94 MB
Release : 2019-06-13
Category : Science
ISBN : 9781641720908

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Spatial analysis refers to the set of analytical approaches and techniques concerned with the study of geographical elements and entities, and their geometric, geographical and topological properties. Some of the issues in spatial analysis involve spatial characterization of entities, spatial dependency and spatial auto-correlation problem, scaling, spatial sampling, etc. The principal types of spatial analysis are spatial data analysis, spatial autocorrelation, spatial interpolation, spatial regression, and simulation and modeling, among many others. The analysis of geospatial data involves statistical analyses using software, geographic information systems (GIS) and geomatics. It has applications in diverse areas like ecology, geology, epidemiology, defense, disaster risk reduction and management, etc. This book provides comprehensive insights into the field of spatial analysis. Most of the topics introduced herein cover new techniques, practices and applications of spatial analysis. Those with an interest in this field would find this textbook helpful.

An Introduction to R for Spatial Analysis and Mapping

Author : Chris Brunsdon
Publisher : SAGE
Page : 386 pages
File Size : 23,47 MB
Release : 2014-04-30
Category : Social Science
ISBN : 1473911192

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"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.

Spatial Analysis Methods and Practice

Author : George Grekousis
Publisher : Cambridge University Press
Page : 535 pages
File Size : 46,27 MB
Release : 2020-06-11
Category : Technology & Engineering
ISBN : 1108585507

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This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences.

Spatial Data Analysis

Author : Manfred M. Fischer
Publisher : Springer Science & Business Media
Page : 85 pages
File Size : 42,97 MB
Release : 2011-08-05
Category : Business & Economics
ISBN : 3642217206

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The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focuses on detecting patterns, and on exploring and modelling relationships between them in order to understand the processes responsible for their emergence. In this way, the role of space is emphasised , and our understanding of the working and representation of space, spatial patterns, and processes is enhanced. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered.

The Practice of Spatial Analysis

Author : Helen Briassoulis
Publisher : Springer
Page : 381 pages
File Size : 20,68 MB
Release : 2018-06-28
Category : Science
ISBN : 331989806X

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This edited volume compiles a set of papers that present various applications of spatial analysis, both traditional and contemporary, on diverse subjects in a wide range of contexts. The volume is dedicated to the memory of the late Professor Pavlos Kanaroglou, McMaster University, Canada, who greatly contributed to scientific and applied research on spatial analysis. In his honor, the book offers a selection of various spatial analysis approaches to the study of contemporary urban transportation, land use, and air pollution issues. The first part of the book discusses selected general issues in spatial analysis; ontologies, agent-based modelling and accessibility analysis. The second part deals with urban transportation analysis and modelling issues; agent-based activity/travel microsimulation, bottleneck models, public transit use, freight transport and connected automated vehicles impact assessment. Part three focuses on integrated land use and transport analysis, discussing the land value impacts of public transport infrastructure, the role of transport provision on business evolution and commute distance considerations in urban relocation. The fourth part, on travel-related air pollution analysis, presents the development of a geo-information software for mapping Aerosol Optical Thickness in urban environments and the development of a neighborhood level, real time, internet-enabled, air pollution map in the Canadian urban context. This book will appeal to academics, researchers, graduate students, consultants, and practitioners working on topics related to spatial analysis, land use and transport analysis, planning and decision making, and air pollution studies.

Machine Learning for Spatial Environmental Data

Author : Mikhail Kanevski
Publisher : EPFL Press
Page : 444 pages
File Size : 18,49 MB
Release : 2009-06-09
Category : Science
ISBN : 9780849382376

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Acompanyament de CD-RM conté MLO software, la guia d'MLO (pdf) i exemples de dades.