Handbook of Spatial AnalysisTheory and Application with R
Insee Méthodes N°131 - October 2018
The United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) “acknowledged the critical importance of integrating geospatial information with statistics and socio-economic data and the development of a geospatial statistical framework”. There is a growing interest in spatial phenomena and, as a consequence, the need for geolocated data is also increasing. To this end, the French national institute of statistics and economic studies (Insee) has undertaken a reshaping of its geographical information system.
Integrating geographical and statistical data is one thing. Analysing such data is another one. To this end, Insee has coordinated, with the strong support of Eurostat and the European Forum for Geography and Statistics, the writing of a handbook of spatial analysis. The handbook draws up the list of analysis that can be carried out with spatial data and the pitfalls to avoid when using them.
The purpose of this handbook of spatial analysis is to answer the questions faced by data analysts in statistical institutes. What are the different usages of the geolocated data sources? In what cases should their spatial dimension be taken into account? How should spatial statistical and econometric methods be applied? Unlike existing manuals, this handbook has been expressly designed according to the issues specific to statistical institutes, such as spatial sampling, spatial econometrics, confidentiality or spatial smoothing.
The handbook is divided into four parts and fourteen chapters. The first three chapters match the stages one would follow to carry out a study with spatial data: describing the location of the observations, measuring spatial interactions and applying the appropriate model. Each chapter explains the theoretical foundations, gives practical applications based on data coming from public statistical institutes, and displays how to use the R statistical software to carry out the computations.
Table of contents (pdf, 27 Ko)
Foreword EFGS - EUROSTAT (pdf, 79 Ko)
INSEE Editorial - reader's guide (pdf, 88 Ko)
Authors and reviewers (pdf, 77 Ko)
Part 1: Describing geolocalized data
Chapter 1. Descriptive Spatial Analysis (pdf, 2 Mo)
Chapter 2. Codifying the neighbourhood structure (pdf, 1 Mo)
Part 2: Measuring the importance of spatial effects
Chapter 3. Spatial autocorrelation indices (pdf, 1 Mo)
Chapter 4. Spatial distribution of points (pdf, 640 Ko)
Chapter 5. Geostatistics (pdf, 850 Ko)
Part 3: Taking spatial effects into account
Chapter 6. Spatial econometrics - common models (pdf, 617 Ko)
Chapter 7. Spatial econometrics on panel data (pdf, 1 Mo)
Chapter 8. Spatial smoothing (pdf, 9 Mo)
Chapter 9. Geographically Weighted Regression (pdf, 2 Mo)
Chapter 10. Spatial sampling (pdf, 1 Mo)
Chapter 11. Spatial econometrics on survey data (pdf, 5 Mo)
Chapter 12. Small areas ans spatial correlation (pdf, 348 Ko)
Part 4: Extensions
Chapter 13. Graph partitioning and analysis (pdf, 775 Ko)
Chapter 14. Confidentiality of spatial data (pdf, 706 Ko)
Index (pdf, 93 Ko)