Roger S. Bivand Edzer J. Pebesma Virgilio Gömez-Rubio. Applied Spatial Data Analysis with R. 4:1 Springer
|
|
- Jeffrey Dennis
- 5 years ago
- Views:
Transcription
1 Roger S. Bivand Edzer J. Pebesma Virgilio Gömez-Rubio Applied Spatial Data Analysis with R 4:1 Springer
2 Contents Preface VII 1 Hello World: Introducing Spatial Data Applied Spatial Data Analysis Why Do We Use R In General? for Spatial Data Analysis? R and GIS What is GIS? Service-Oriented Architectures Further Reading an GIS Types of Spatial Data Storage and Display Applied Spatial Data Analysis R Spatial Resources Online Resources Layout of the Book 14 Part I Handling Spatial Data in R 2 Classes for Spatial Data in R Introduction Classes and Methods in R Spat ial Objects Spat ia1p o int s Methods Data Frames for Spatial Point Data Spat ianines 38
3 X Contents 2.6 Spat lallpolygons SpatialPolygonsDataFrame Objects Holes and Ring Direction Spat ialgr id and Spat ialpixel Objects 47 3 Visualising Spatial Data The Traditional Plot System Plotting Points, Lines, Polygons, and Grids Axes and Layout Elements Degrees in Axes Labels and Reference Grid Plot Size, Plotting Area, Map Scale, and Multiple Plots Plotting Attributes and Map Legends Trellis/Lattice Plots with spplot A Straight Trellis Example Plotting Points, Lines, Polygons, and Grids Adding Reference and Layout Elements to Plots Arranging Panel Layout Interacting with Plots Interacting with Base Graphics Interacting with spplot and Lattice Plots Colour Palettes and Class Intervals Colour Palettes Class Intervals 77 4 Spatial Data Import and Export Coordinate Reference Systems Using the EPSG List PROJ.4 CRS Specification Projection and Transformation Degrees, Minutes, and Seconds Vector File Formats Using OGR Drivers in rgdal Other Import/Export Functions Raster File Formats Using GDAL Drivers in rgdal Writing a Google Earthrm Image Overlay Other Import/Export Functions Grass Broad Street Cholera Data Other Import/Export Interfaces Analysis and Visualisation Applications TerraLib and art Other GIS and Web Mapping Systems Installing rgdal 111
4 Contents XI 5 Further Methods for Handling Spatial Data Support Overlay Spatial Sampling Checking Topologies Dissolving Polygons Checking Hole Status Combining Spatial Data Combining Positional Data Combining Attribute Data Auxiliary Functions Customising Spatial Data Classes and Methods Programming with Classes and Methods S3-Style Classes and Methods Style Classes and Methods Animal Track Data in Package Trip Generic and Constructor Functions Methods for Trip Objects Multi-Point Data: Spat ia1multipoint s Hexagonal Grids Spatio-Temporal Grids Analysing Spatial Monte Carlo Simulations Processing Massive Grids 146 Part II Analysing Spatial Data 7 Spatial Point Pattern Analysis Introduction Packages for the Analysis of Spatial Point Patterns Preliminary Analysis of a Point Pattern Complete Spatial Randomness G Function: Distance to the Nearest Event F Function: Distance from a Point to the Nearest Event Statistical Analysis of Spatial Point Processes Homogeneous Poisson Processes Inhomogeneous Poisson Processes Estimation of the Intensity Likelihood of an Inhomogeneous Poisson Process Second-Order Properties Some Applications in Spatial Epidemiology Case Control Studies Binary Regression Estimator 178
5 XII Contents Binary Regression Using Generalised Additive Models Point Source Pollution Accounting for Confounding and Covariates Further Methods for the Analysis of Point Patterns Interpolation and Geostatistics Introduction Exploratory Data Analysis Non-Geostatistical Interpolation Methods Inverse Distance Weighted Interpolation Linear Regression Estimating Spatial Correlation: The Variogram Exploratory Variogram Analysis Cutoff, Lag Width, Direction Dependence Variogram Modelling Anisotropy Multivariable Variogram Modelling Residual Variogram Modelling Spatial Prediction Universal, Ordinary, and Simple Kriging Multivariable Prediction: Cokriging Collocated Cokriging Cokriging Contrasts Kriging in a Local Neighbourhood Change of Support: Block Kriging Stratifying the Domain Trend Functions and their Coefficients Non-Linear Transforms of the Response Variable Singular Matrix Errors Model Diagnostics Cross Validation Residuals Cross Validation z-scores Multivariable Cross Validation Limit ations to Cross Validation Geostatistical Simulation Sequential Simulation Non-Linear Spatial Aggregation and Block Averages Multivariable and Indicator Simulation Model-Based Geostatistics and Bayesian Approaches Monitoring Network Optimization Other R Packages for Interpolation and Geostatistics Non-Geostatistical Interpolation spatial RandomFields geor and georglm fields 235
6 Contents XIII 9 Areal Data and Spatial Autocorrelation Introduction Spatial Neighbours Neighbour Objects Creating Contiguity Neighbours Creating Graph-Based Neighbours Distance-Based Neighbours Higher-Order Neighbours Grid Neighbours Spatial Weights Spatial Weights Styles General Spatial Weights Importing, Converting, and Exporting Spatial Neighbours and Weights Using Weights to Simulate Spatial Autocorrelation Manipulating Spatial Weights Spatial Autocorrelation: Tests Global Tests Local Tests Modelling Areal Data Introduction Spatial Statistics Approaches Simultaneous Autoregressive Models Conditional Autoregressive Models Fitting Spatial Regression Models Mixed-Effects Models Spatial Econometrics Approaches Other Methods GAM, GEE, GLMM Moran Eigenvectors Geographically Weighted Regression Disease Mapping Introduction Statistical Models Poisson-Gamma Model Log-Normal Model Marshall's Global EB Estimator Spatially Structured Statistical Models Bayesian Hierarchical Models The Poisson-Gamma Model Revisited Spatial Models Detection of Clusters of Disease Testing the Homogeneity of the Relative Risks Moran's I Test of Spatial Autocorrelation 335
7 XIV Contents Tango's Test of General Clustering Detection of the Location of a Cluster Geographical Analysis Machine Kulldorff's Statistic Stone's Test for Localised Clusters Other Topics in Disease Mapping 341 Afterword 343 R and Package Versions Used 344 Data Sets Used 344 References 347 Subject Index 361 Functions Index 371
Use R! Series Editors: Robert Gentleman Kurt Hornik Giovanni Parmigiani
Use R! Series Editors: Robert Gentleman Kurt Hornik Giovanni Parmigiani Use R! Albert: Bayesian Computation with R Bivand/Pebesma/Gómez-Rubio: Applied Spatial Data Analysis with R Cook/Swayne: Interactive
More informationStatistícal Methods for Spatial Data Analysis
Texts in Statistícal Science Statistícal Methods for Spatial Data Analysis V- Oliver Schabenberger Carol A. Gotway PCT CHAPMAN & K Contents Preface xv 1 Introduction 1 1.1 The Need for Spatial Analysis
More informationSpatial Analysis 1. Introduction
Spatial Analysis 1 Introduction Geo-referenced Data (not any data) x, y coordinates (e.g., lat., long.) ------------------------------------------------------ - Table of Data: Obs. # x y Variables -------------------------------------
More informationI don t have much to say here: data are often sampled this way but we more typically model them in continuous space, or on a graph
Spatial analysis Huge topic! Key references Diggle (point patterns); Cressie (everything); Diggle and Ribeiro (geostatistics); Dormann et al (GLMMs for species presence/abundance); Haining; (Pinheiro and
More informationGeometric Algorithms in GIS
Geometric Algorithms in GIS GIS Software Dr. M. Gavrilova GIS System What is a GIS system? A system containing spatially referenced data that can be analyzed and converted to new information for a specific
More informationOutline. Introduction to SpaceStat and ESTDA. ESTDA & SpaceStat. Learning Objectives. Space-Time Intelligence System. Space-Time Intelligence System
Outline I Data Preparation Introduction to SpaceStat and ESTDA II Introduction to ESTDA and SpaceStat III Introduction to time-dynamic regression ESTDA ESTDA & SpaceStat Learning Objectives Activities
More informationFindings from a Search for R Spatial Analysis Support. Donald L. Schrupp Wildlife Ecologist Colorado Division of Wildlife (Retired)
Findings from a Search for R Spatial Analysis Support Donald L. Schrupp Wildlife Ecologist Colorado Division of Wildlife (Retired) Findings from a Search for R Spatial Analysis Support === Approach Steps
More informationContents 1 Introduction 2 Statistical Tools and Concepts
1 Introduction... 1 1.1 Objectives and Approach... 1 1.2 Scope of Resource Modeling... 2 1.3 Critical Aspects... 2 1.3.1 Data Assembly and Data Quality... 2 1.3.2 Geologic Model and Definition of Estimation
More informationMichael Harrigan Office hours: Fridays 2:00-4:00pm Holden Hall
Announcement New Teaching Assistant Michael Harrigan Office hours: Fridays 2:00-4:00pm Holden Hall 209 Email: michael.harrigan@ttu.edu Guofeng Cao, Texas Tech GIST4302/5302, Lecture 2: Review of Map Projection
More informationGstat: multivariable geostatistics for S
DSC 2003 Working Papers (Draft Versions) http://www.ci.tuwien.ac.at/conferences/dsc-2003/ Gstat: multivariable geostatistics for S Edzer J. Pebesma Dept. of Physical Geography, Utrecht University, P.O.
More informationGIST 4302/5302: Spatial Analysis and Modeling
GIST 4302/5302: Spatial Analysis and Modeling Review Guofeng Cao www.gis.ttu.edu/starlab Department of Geosciences Texas Tech University guofeng.cao@ttu.edu Spring 2016 Course Outlines Spatial Point Pattern
More informationWEB application for the analysis of spatio-temporal data
EXTERNAL SCIENTIFIC REPORT APPROVED: 17 October 2016 WEB application for the analysis of spatio-temporal data Abstract Machteld Varewyck (Open Analytics NV), Tobias Verbeke (Open Analytics NV) In specific
More informationSpatial Statistics A Framework for Analyzing Geographically Referenced Data in Insurance Ratemaking
Spatial Statistics A Framework for Analyzing Geographically Referenced Data in Insurance Ratemaking Satadru Sengupta Personal Market Liberty Mutual Group CAS Ratemaking & Product Management Seminar Chicago
More informationGIST 4302/5302: Spatial Analysis and Modeling Lecture 2: Review of Map Projections and Intro to Spatial Analysis
GIST 4302/5302: Spatial Analysis and Modeling Lecture 2: Review of Map Projections and Intro to Spatial Analysis Guofeng Cao http://www.spatial.ttu.edu Department of Geosciences Texas Tech University guofeng.cao@ttu.edu
More informationGIST 4302/5302: Spatial Analysis and Modeling
GIST 4302/5302: Spatial Analysis and Modeling Lecture 2: Review of Map Projections and Intro to Spatial Analysis Guofeng Cao http://thestarlab.github.io Department of Geosciences Texas Tech University
More informationSpatial Point Pattern Analysis
Spatial Point Pattern Analysis Jamie Monogan University of Georgia Spatial Data Analysis Jamie Monogan (UGA) Spatial Point Pattern Analysis Spatial Data Analysis 1 / 13 Objectives By the end of this meeting,
More informationAnalysing Spatial Data in R: Why spatial data in R?
Analysing Spatial Data in R: Why spatial data in R? Roger Bivand Department of Economics Norwegian School of Economics and Business Administration Bergen, Norway 31 August 2007 Why spatial data in R? What
More informationCommunity Health Needs Assessment through Spatial Regression Modeling
Community Health Needs Assessment through Spatial Regression Modeling Glen D. Johnson, PhD CUNY School of Public Health glen.johnson@lehman.cuny.edu Objectives: Assess community needs with respect to particular
More informationVisualize and interactively design weight matrices
Visualize and interactively design weight matrices Angelos Mimis *1 1 Department of Economic and Regional Development, Panteion University of Athens, Greece Tel.: +30 6936670414 October 29, 2014 Summary
More informationBAYESIAN MODEL FOR SPATIAL DEPENDANCE AND PREDICTION OF TUBERCULOSIS
BAYESIAN MODEL FOR SPATIAL DEPENDANCE AND PREDICTION OF TUBERCULOSIS Srinivasan R and Venkatesan P Dept. of Statistics, National Institute for Research Tuberculosis, (Indian Council of Medical Research),
More informationGIS CONCEPTS ARCGIS METHODS AND. 2 nd Edition, July David M. Theobald, Ph.D. Natural Resource Ecology Laboratory Colorado State University
GIS CONCEPTS AND ARCGIS METHODS 2 nd Edition, July 2005 David M. Theobald, Ph.D. Natural Resource Ecology Laboratory Colorado State University Copyright Copyright 2005 by David M. Theobald. All rights
More informationSpatial Analysis with ArcGIS Pro STUDENT EDITION
Spatial Analysis with ArcGIS Pro STUDENT EDITION Copyright 2018 Esri All rights reserved. Course version 2.0. Version release date November 2018. Printed in the United States of America. The information
More informationLecture 5 Geostatistics
Lecture 5 Geostatistics Lecture Outline Spatial Estimation Spatial Interpolation Spatial Prediction Sampling Spatial Interpolation Methods Spatial Prediction Methods Interpolating Raster Surfaces with
More informationGstat: Multivariable Geostatistics for S
New URL: http://www.r-project.org/conferences/dsc-2003/ Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003) March 20 22, Vienna, Austria ISSN 1609-395X Kurt Hornik,
More informationIndex. Geostatistics for Environmental Scientists, 2nd Edition R. Webster and M. A. Oliver 2007 John Wiley & Sons, Ltd. ISBN:
Index Akaike information criterion (AIC) 105, 290 analysis of variance 35, 44, 127 132 angular transformation 22 anisotropy 59, 99 affine or geometric 59, 100 101 anisotropy ratio 101 exploring and displaying
More informationStatistics: A review. Why statistics?
Statistics: A review Why statistics? What statistical concepts should we know? Why statistics? To summarize, to explore, to look for relations, to predict What kinds of data exist? Nominal, Ordinal, Interval
More informationGeostatistics for Seismic Data Integration in Earth Models
2003 Distinguished Instructor Short Course Distinguished Instructor Series, No. 6 sponsored by the Society of Exploration Geophysicists European Association of Geoscientists & Engineers SUB Gottingen 7
More informationIntroduction to Spatial Analysis. Spatial Analysis. Session organization. Learning objectives. Module organization. GIS and spatial analysis
Introduction to Spatial Analysis I. Conceptualizing space Session organization Module : Conceptualizing space Module : Spatial analysis of lattice data Module : Spatial analysis of point patterns Module
More informationTypes of Spatial Data
Spatial Data Types of Spatial Data Point pattern Point referenced geostatistical Block referenced Raster / lattice / grid Vector / polygon Point Pattern Data Interested in the location of points, not their
More informationHurricane Climatology
Hurricane Climatology Elsner: 00 ELSNER PRELIMS 2012/9/25 18:12 page i #1 Elsner: 00 ELSNER PRELIMS 2012/9/25 18:12 page ii #2 Hurricane Climatology A Modern Statistical Guide Using R James B. Elsner and
More informationOpen Source Geospatial Software - an Introduction Spatial Programming with R
Open Source Geospatial Software - an Introduction Spatial Programming with R V. Gómez-Rubio Based on some course notes by Roger S. Bivand Departamento de Matemáticas Universidad de Castilla-La Mancha 17-18
More informationLuc Anselin Spatial Analysis Laboratory Dept. Agricultural and Consumer Economics University of Illinois, Urbana-Champaign
GIS and Spatial Analysis Luc Anselin Spatial Analysis Laboratory Dept. Agricultural and Consumer Economics University of Illinois, Urbana-Champaign http://sal.agecon.uiuc.edu Outline GIS and Spatial Analysis
More informationContents. Preface. Introduction 1 Manfred M. Fischer and Arthur Getis. GI Software Tools
Contents Preface v Introduction 1 Manfred M. Fischer and Arthur Getis PART A GI Software Tools A.1 Spatial Statistics in ArcGIS Lauren M. Scott and Mark V. Janikas A.1.1 Introduction 27 A.1.2 Measuring
More informationSummary STK 4150/9150
STK4150 - Intro 1 Summary STK 4150/9150 Odd Kolbjørnsen May 22 2017 Scope You are expected to know and be able to use basic concepts introduced in the book. You knowledge is expected to be larger than
More informationAn Introduction to Pattern Statistics
An Introduction to Pattern Statistics Nearest Neighbors The CSR hypothesis Clark/Evans and modification Cuzick and Edwards and controls All events k function Weighted k function Comparative k functions
More informationSPATIO-TEMPORAL REGRESSION MODELS FOR DEFORESTATION IN THE BRAZILIAN AMAZON
SPATIO-TEMPORAL REGRESSION MODELS FOR DEFORESTATION IN THE BRAZILIAN AMAZON Giovana M. de Espindola a, Edzer Pebesma b,c1, Gilberto Câmara a a National institute for space research (INPE), Brazil b Institute
More informationIntroduction to IsoMAP Isoscapes Modeling, Analysis, and Prediction
Introduction to IsoMAP Isoscapes Modeling, Analysis, and Prediction What is IsoMAP To the user, and online workspace for: Accessing, manipulating, and analyzing, and modeling environmental isotope data
More informationAn Introduction to Spatial Statistics. Chunfeng Huang Department of Statistics, Indiana University
An Introduction to Spatial Statistics Chunfeng Huang Department of Statistics, Indiana University Microwave Sounding Unit (MSU) Anomalies (Monthly): 1979-2006. Iron Ore (Cressie, 1986) Raw percent data
More informationSPACE Workshop NSF NCGIA CSISS UCGIS SDSU. Aldstadt, Getis, Jankowski, Rey, Weeks SDSU F. Goodchild, M. Goodchild, Janelle, Rebich UCSB
SPACE Workshop NSF NCGIA CSISS UCGIS SDSU Aldstadt, Getis, Jankowski, Rey, Weeks SDSU F. Goodchild, M. Goodchild, Janelle, Rebich UCSB August 2-8, 2004 San Diego State University Some Examples of Spatial
More informationEconometric Analysis of Cross Section and Panel Data
Econometric Analysis of Cross Section and Panel Data Jeffrey M. Wooldridge / The MIT Press Cambridge, Massachusetts London, England Contents Preface Acknowledgments xvii xxiii I INTRODUCTION AND BACKGROUND
More informationEstimating the long-term health impact of air pollution using spatial ecological studies. Duncan Lee
Estimating the long-term health impact of air pollution using spatial ecological studies Duncan Lee EPSRC and RSS workshop 12th September 2014 Acknowledgements This is joint work with Alastair Rushworth
More informationGeneralized Linear. Mixed Models. Methods and Applications. Modern Concepts, Walter W. Stroup. Texts in Statistical Science.
Texts in Statistical Science Generalized Linear Mixed Models Modern Concepts, Methods and Applications Walter W. Stroup CRC Press Taylor & Francis Croup Boca Raton London New York CRC Press is an imprint
More informationA Partial List 1 of R packages for doing Spatial Data Analysis
1 A Partial List 1 of R packages for doing Spatial Data Analysis ade4 Multivariate data analysis and graphical display [Includes Moran s I and Geary s C; multivariate spatial analysis] adegenet Classes
More informationChapter 4 - Spatial processes R packages and software Lecture notes
TK4150 - Intro 1 Chapter 4 - Spatial processes R packages and software Lecture notes Odd Kolbjørnsen and Geir Storvik February 13, 2017 STK4150 - Intro 2 Last time General set up for Kriging type problems
More informationAvailable online at ScienceDirect. Procedia Environmental Sciences 27 (2015 ) Roger Bivand a,b,
Available online at www.sciencedirect.com ScienceDirect Procedia Environmental Sciences 27 (2015 ) 106 111 Spatial Statistics 2015: Emerging Patterns - Part 2 Spatialdiffusion and spatial statistics: revisting
More informationMultilevel Statistical Models: 3 rd edition, 2003 Contents
Multilevel Statistical Models: 3 rd edition, 2003 Contents Preface Acknowledgements Notation Two and three level models. A general classification notation and diagram Glossary Chapter 1 An introduction
More informationSpatial Analysis I. Spatial data analysis Spatial analysis and inference
Spatial Analysis I Spatial data analysis Spatial analysis and inference Roadmap Outline: What is spatial analysis? Spatial Joins Step 1: Analysis of attributes Step 2: Preparing for analyses: working with
More informationSUT WA Research Night
SUT WA Research Night An introduction to acoustic seafloor observation and geostatistical data interpolation Elizabeth Mair BSc (GIS) Honours Curtin University Contents Project Introduction Methodology
More informationChapter 6 Spatial Analysis
6.1 Introduction Chapter 6 Spatial Analysis Spatial analysis, in a narrow sense, is a set of mathematical (and usually statistical) tools used to find order and patterns in spatial phenomena. Spatial patterns
More informationAcknowledgments xiii Preface xv. GIS Tutorial 1 Introducing GIS and health applications 1. What is GIS? 2
Acknowledgments xiii Preface xv GIS Tutorial 1 Introducing GIS and health applications 1 What is GIS? 2 Spatial data 2 Digital map infrastructure 4 Unique capabilities of GIS 5 Installing ArcView and the
More informationFORECASTING METHODS AND APPLICATIONS SPYROS MAKRIDAKIS STEVEN С WHEELWRIGHT. European Institute of Business Administration. Harvard Business School
FORECASTING METHODS AND APPLICATIONS SPYROS MAKRIDAKIS European Institute of Business Administration (INSEAD) STEVEN С WHEELWRIGHT Harvard Business School. JOHN WILEY & SONS SANTA BARBARA NEW YORK CHICHESTER
More informationGIST 4302/5302: Spatial Analysis and Modeling
GIST 4302/5302: Spatial Analysis and Modeling Spring 2014 Lectures: Tuesdays & Thursdays 2:00pm-2:50pm, Holden Hall 00038 Lab sessions: Tuesdays or Thursdays 3:00pm-4:50pm or Wednesday 1:00pm-2:50pm, Holden
More informationWhat s special about spatial data?
What s special about spatial data? Road map Geographic Information analysis The need to develop spatial thinking Some fundamental geographic concepts (PBCS) What are the effects of space? Spatial autocorrelation
More informationAn Introduction to Applied Multivariate Analysis with R
~ Snrinuer Brian Everitt Torsten Hathorn An Introduction to Applied Multivariate Analysis with R > Preface........................................................ vii 1 Multivariate Data and Multivariate
More informationThe Nature of Geographic Data
4 The Nature of Geographic Data OVERVIEW Elaborates on the spatial is special theme Focuses on how phenomena vary across space and the general nature of geographic variation Describes the main principles
More informationAdvanced analysis and modelling tools for spatial environmental data. Case study: indoor radon data in Switzerland
EnviroInfo 2004 (Geneva) Sh@ring EnviroInfo 2004 Advanced analysis and modelling tools for spatial environmental data. Case study: indoor radon data in Switzerland Mikhail Kanevski 1, Michel Maignan 1
More informationCombining Incompatible Spatial Data
Combining Incompatible Spatial Data Carol A. Gotway Crawford Office of Workforce and Career Development Centers for Disease Control and Prevention Invited for Quantitative Methods in Defense and National
More informationSpatial Data Mining. Regression and Classification Techniques
Spatial Data Mining Regression and Classification Techniques 1 Spatial Regression and Classisfication Discrete class labels (left) vs. continues quantities (right) measured at locations (2D for geographic
More informationRonald Christensen. University of New Mexico. Albuquerque, New Mexico. Wesley Johnson. University of California, Irvine. Irvine, California
Texts in Statistical Science Bayesian Ideas and Data Analysis An Introduction for Scientists and Statisticians Ronald Christensen University of New Mexico Albuquerque, New Mexico Wesley Johnson University
More informationEXPLORATORY SPATIAL DATA ANALYSIS OF BUILDING ENERGY IN URBAN ENVIRONMENTS. Food Machinery and Equipment, Tianjin , China
EXPLORATORY SPATIAL DATA ANALYSIS OF BUILDING ENERGY IN URBAN ENVIRONMENTS Wei Tian 1,2, Lai Wei 1,2, Pieter de Wilde 3, Song Yang 1,2, QingXin Meng 1 1 College of Mechanical Engineering, Tianjin University
More informationAggregated cancer incidence data: spatial models
Aggregated cancer incidence data: spatial models 5 ième Forum du Cancéropôle Grand-est - November 2, 2011 Erik A. Sauleau Department of Biostatistics - Faculty of Medicine University of Strasbourg ea.sauleau@unistra.fr
More informationToward an automatic real-time mapping system for radiation hazards
Toward an automatic real-time mapping system for radiation hazards Paul H. Hiemstra 1, Edzer J. Pebesma 2, Chris J.W. Twenhöfel 3, Gerard B.M. Heuvelink 4 1 Faculty of Geosciences / University of Utrecht
More informationChapter 1. Summer School GEOSTAT 2014, Spatio-Temporal Geostatistics,
Chapter 1 Summer School GEOSTAT 2014, Geostatistics, 2014-06-19 sum- http://ifgi.de/graeler Institute for Geoinformatics University of Muenster 1.1 Spatial Data From a purely statistical perspective, spatial
More informationAnalysis of Interest Rate Curves Clustering Using Self-Organising Maps
Analysis of Interest Rate Curves Clustering Using Self-Organising Maps M. Kanevski (1), V. Timonin (1), A. Pozdnoukhov(1), M. Maignan (1,2) (1) Institute of Geomatics and Analysis of Risk (IGAR), University
More informationGIST 4302/5302: Spatial Analysis and Modeling
GIST 4302/5302: Spatial Analysis and Modeling Spring 2016 Lectures: Tuesdays & Thursdays 12:30pm-1:20pm, Science 234 Labs: GIST 4302: Monday 1:00-2:50pm or Tuesday 2:00-3:50pm GIST 5302: Wednesday 2:00-3:50pm
More informationGIST 4302/5302: Spatial Analysis and Modeling
GIST 4302/5302: Spatial Analysis and Modeling Fall 2015 Lectures: Tuesdays & Thursdays 2:00pm-2:50pm, Science 234 Lab sessions: Tuesdays or Thursdays 3:00pm-4:50pm or Friday 9:00am-10:50am, Holden 204
More informationSpatial Data, Spatial Analysis and Spatial Data Science
Spatial Data, Spatial Analysis and Spatial Data Science Luc Anselin http://spatial.uchicago.edu 1 spatial thinking in the social sciences spatial analysis spatial data science spatial data types and research
More informationImproving Spatial Data Interoperability
Improving Spatial Data Interoperability A Framework for Geostatistical Support-To To-Support Interpolation Michael F. Goodchild, Phaedon C. Kyriakidis, Philipp Schneider, Matt Rice, Qingfeng Guan, Jordan
More informationThe Use of Spatial Weights Matrices and the Effect of Geometry and Geographical Scale
The Use of Spatial Weights Matrices and the Effect of Geometry and Geographical Scale António Manuel RODRIGUES 1, José António TENEDÓRIO 2 1 Research fellow, e-geo Centre for Geography and Regional Planning,
More informationSpatial Regression. 1. Introduction and Review. Luc Anselin. Copyright 2017 by Luc Anselin, All Rights Reserved
Spatial Regression 1. Introduction and Review Luc Anselin http://spatial.uchicago.edu matrix algebra basics spatial econometrics - definitions pitfalls of spatial analysis spatial autocorrelation spatial
More informationIntroduction GeoXp : an R package for interactive exploratory spatial data analysis. Illustration with a data set of schools in Midi-Pyrénées.
Presentation of Presentation of Use of Introduction : an R package for interactive exploratory spatial data analysis. Illustration with a data set of schools in Midi-Pyrénées. Authors of : Christine Thomas-Agnan,
More informationAnalysing Spatial Data in R: Worked example: geostatistics
Analysing Spatial Data in R: Worked example: geostatistics Roger Bivand Department of Economics Norwegian School of Economics and Business Administration Bergen, Norway 17 April 2007 Worked example: geostatistics
More informationBayesian Hierarchical Models
Bayesian Hierarchical Models Gavin Shaddick, Millie Green, Matthew Thomas University of Bath 6 th - 9 th December 2016 1/ 34 APPLICATIONS OF BAYESIAN HIERARCHICAL MODELS 2/ 34 OUTLINE Spatial epidemiology
More informationGIS CONCEPTS ARCGIS METHODS AND. 3 rd Edition, July David M. Theobald, Ph.D. Warner College of Natural Resources Colorado State University
GIS CONCEPTS AND ARCGIS METHODS 3 rd Edition, July 2007 David M. Theobald, Ph.D. Warner College of Natural Resources Colorado State University Copyright Copyright 2007 by David M. Theobald. All rights
More informationFrom Practical Data Analysis with JMP, Second Edition. Full book available for purchase here. About This Book... xiii About The Author...
From Practical Data Analysis with JMP, Second Edition. Full book available for purchase here. Contents About This Book... xiii About The Author... xxiii Chapter 1 Getting Started: Data Analysis with JMP...
More informationCluster Analysis using SaTScan
Cluster Analysis using SaTScan Summary 1. Statistical methods for spatial epidemiology 2. Cluster Detection What is a cluster? Few issues 3. Spatial and spatio-temporal Scan Statistic Methods Probability
More informationMultivariate Geostatistics
Hans Wackernagel Multivariate Geostatistics An Introduction with Applications Third, completely revised edition with 117 Figures and 7 Tables Springer Contents 1 Introduction A From Statistics to Geostatistics
More information4th HR-HU and 15th HU geomathematical congress Geomathematics as Geoscience Reliability enhancement of groundwater estimations
Reliability enhancement of groundwater estimations Zoltán Zsolt Fehér 1,2, János Rakonczai 1, 1 Institute of Geoscience, University of Szeged, H-6722 Szeged, Hungary, 2 e-mail: zzfeher@geo.u-szeged.hu
More informationPreface Introduction to Statistics and Data Analysis Overview: Statistical Inference, Samples, Populations, and Experimental Design The Role of
Preface Introduction to Statistics and Data Analysis Overview: Statistical Inference, Samples, Populations, and Experimental Design The Role of Probability Sampling Procedures Collection of Data Measures
More informationA Geostatistical Approach to Linking Geographically-Aggregated Data From Different Sources
A Geostatistical Approach to Linking Geographically-Aggregated Data From Different Sources Carol A. Gotway Crawford National Center for Environmental Health Centers for Disease Control and Prevention,
More informationUSING CLUSTERING SOFTWARE FOR EXPLORING SPATIAL AND TEMPORAL PATTERNS IN NON-COMMUNICABLE DISEASES
USING CLUSTERING SOFTWARE FOR EXPLORING SPATIAL AND TEMPORAL PATTERNS IN NON-COMMUNICABLE DISEASES Mariana Nagy "Aurel Vlaicu" University of Arad Romania Department of Mathematics and Computer Science
More informationAnimating Maps: Visual Analytics meets Geoweb 2.0
Animating Maps: Visual Analytics meets Geoweb 2.0 Piyush Yadav 1, Shailesh Deshpande 1, Raja Sengupta 2 1 Tata Research Development and Design Centre, Pune (India) Email: {piyush.yadav1, shailesh.deshpande}@tcs.com
More informationSPATIAL ECONOMETRICS: METHODS AND MODELS
SPATIAL ECONOMETRICS: METHODS AND MODELS STUDIES IN OPERATIONAL REGIONAL SCIENCE Folmer, H., Regional Economic Policy. 1986. ISBN 90-247-3308-1. Brouwer, F., Integrated Environmental Modelling: Design
More informationPerformance Analysis of Some Machine Learning Algorithms for Regression Under Varying Spatial Autocorrelation
Performance Analysis of Some Machine Learning Algorithms for Regression Under Varying Spatial Autocorrelation Sebastian F. Santibanez Urban4M - Humboldt University of Berlin / Department of Geography 135
More informationBayesian SAE using Complex Survey Data Lecture 4A: Hierarchical Spatial Bayes Modeling
Bayesian SAE using Complex Survey Data Lecture 4A: Hierarchical Spatial Bayes Modeling Jon Wakefield Departments of Statistics and Biostatistics University of Washington 1 / 37 Lecture Content Motivation
More informationObjectives Define spatial statistics Introduce you to some of the core spatial statistics tools available in ArcGIS 9.3 Present a variety of example a
Introduction to Spatial Statistics Opportunities for Education Lauren M. Scott, PhD Mark V. Janikas, PhD Lauren Rosenshein Jorge Ruiz-Valdepeña 1 Objectives Define spatial statistics Introduce you to some
More informationEdzer Pebesma (ifgi) Dan Cornford (AST) Gregoire Dubois (EC DG JRC) ifgi. Institute for Geoinformatics University of Münster
Automated mapping of environmental variables from a SISE and SEIS perspective 1. Das neue IfGI-Logo 1.6 Logovarianten Edzer Pebesma (ifgi) Dan Cornford (AST) Gregoire Dubois (EC DG JRC) Logo für den Einsatz
More informationCreating and Managing a W Matrix
Creating and Managing a W Matrix Carlos Hurtado Department of Economics University of Illinois at Urbana-Champaign hrtdmrt2@illinois.edu Junel 22th, 2016 C. Hurtado (UIUC - Economics) Spatial Econometrics
More informationDesign and implementation of a new meteorology geographic information system
Design and implementation of a new meteorology geographic information system WeiJiang Zheng, Bing. Luo, Zhengguang. Hu, Zhongliang. Lv National Meteorological Center, China Meteorological Administration,
More informationLecture 1 Introduction to GIS. Dr. Zhang Spring, 2017
Lecture 1 Introduction to GIS Dr. Zhang Spring, 2017 Topics of the course Using and making maps Navigating GIS Map design Working with spatial data Geoprocessing Spatial data infrastructure Digitizing
More informationBeta-Binomial Kriging: An Improved Model for Spatial Rates
Available online at www.sciencedirect.com ScienceDirect Procedia Environmental Sciences 27 (2015 ) 30 37 Spatial Statistics 2015: Emerging Patterns - Part 2 Beta-Binomial Kriging: An Improved Model for
More informationContents. Preface to Second Edition Preface to First Edition Abbreviations PART I PRINCIPLES OF STATISTICAL THINKING AND ANALYSIS 1
Contents Preface to Second Edition Preface to First Edition Abbreviations xv xvii xix PART I PRINCIPLES OF STATISTICAL THINKING AND ANALYSIS 1 1 The Role of Statistical Methods in Modern Industry and Services
More informationSpatial Clusters of Rates
Spatial Clusters of Rates Luc Anselin http://spatial.uchicago.edu concepts EBI local Moran scan statistics Concepts Rates as Risk from counts (spatially extensive) to rates (spatially intensive) rate =
More informationModels for spatial data (cont d) Types of spatial data. Types of spatial data (cont d) Hierarchical models for spatial data
Hierarchical models for spatial data Based on the book by Banerjee, Carlin and Gelfand Hierarchical Modeling and Analysis for Spatial Data, 2004. We focus on Chapters 1, 2 and 5. Geo-referenced data arise
More informationMapping and Analysis for Spatial Social Science
Mapping and Analysis for Spatial Social Science Luc Anselin Spatial Analysis Laboratory Dept. Agricultural and Consumer Economics University of Illinois, Urbana-Champaign http://sal.agecon.uiuc.edu Outline
More informationPredicting Long-term Exposures for Health Effect Studies
Predicting Long-term Exposures for Health Effect Studies Lianne Sheppard Adam A. Szpiro, Johan Lindström, Paul D. Sampson and the MESA Air team University of Washington CMAS Special Session, October 13,
More informationDevelopment of Integrated Spatial Analysis System Using Open Sources. Hisaji Ono. Yuji Murayama
Development of Integrated Spatial Analysis System Using Open Sources Hisaji Ono PASCO Corporation 1-1-2, Higashiyama, Meguro-ku, TOKYO, JAPAN; Telephone: +81 (03)3421 5846 FAX: +81 (03)3421 5846 Email:
More informationKernel-based Approximation. Methods using MATLAB. Gregory Fasshauer. Interdisciplinary Mathematical Sciences. Michael McCourt.
SINGAPORE SHANGHAI Vol TAIPEI - Interdisciplinary Mathematical Sciences 19 Kernel-based Approximation Methods using MATLAB Gregory Fasshauer Illinois Institute of Technology, USA Michael McCourt University
More informationQGIS FLO-2D Integration
EPiC Series in Engineering Volume 3, 2018, Pages 1575 1583 Engineering HIC 2018. 13th International Conference on Hydroinformatics Karen O Brien, BSc. 1, Noemi Gonzalez-Ramirez, Ph. D. 1 and Fernando Nardi,
More informationContents. Preface to the Third Edition (2007) Preface to the Second Edition (1992) Preface to the First Edition (1985) License and Legal Information
Contents Preface to the Third Edition (2007) Preface to the Second Edition (1992) Preface to the First Edition (1985) License and Legal Information xi xiv xvii xix 1 Preliminaries 1 1.0 Introduction.............................
More information