geoxp: an r package for exploratory spatial data analysis ... · geoxp: an r package for...

GeoXp: an R package for exploratory spatial Data analysis

GeoXp: an R package for exploratory spatial Dataanalysis

Spatial Econometric Association Conference - Toulouse 2011

Thibault LAURENT, Anne RUIZ-GAZEN and ChristineTHOMAS-AGNAN

GREMAQ, Toulouse School of Economics

7 juillet 2011

T. Laurent, A. Ruiz-Gazen and C. Thomas-Agnan GeoXp: an R package for exploratory spatial Data analysis


1 Introduction

2 Spatial statistics with R

3 GeoXp : Interactivity between statistic plots with maps

4 An application on real data

5 Innovations of GeoXp

6 Perspectives



Introduction

Data Set

A data set of n observations and p variables (discrete, continuous) :

VariablesIndividuals 1 . . . p

1 x11 . . . x1p2 x21 . . . x2p...

... . . ....

n xn1 . . . xnp

Each observation is associated to a a spatial object (a point, a lineor a polygon).



Introduction

Definition and objectives of Spatial Exploratory DataAnalysis (SEDA)

Definition : combine information given by techniques of EDAwith spatial information using mapping, interactivity betweenstatistical plots with maps or by creating new methods usingfor example neighborhood matrices.

Objectives : give qualitative response to the usual problems ofspatial analysis like detection of spatial autocorrelation,detection of local or global extreme values, detection ofspatial heterogeneity...



Introduction

SEDA softwares

Because GIS do not take into account enough statisticalmethodology, researchers in spatial statistics have developedsoftwares which take into account this methodology :

GeoDa (L. Anselin, https://www.geoda.uiuc.edu/)

Spatial Econometric Toolbox on Matlab (K. Pace - J. LeSage,http://www.spatial-econometrics.com/)

Many R packages (R. Bivand maintains the spatial Task Viewshttp://cran.r-project.org/web/views/Spatial.html -see also the R Wikihttp://wiki.r-project.org/rwiki/doku.php?id=tips:

spatial-data).

Spatial Econometric with Gauss


https://www.geoda.uiuc.edu/

http://www.spatial-econometrics.com/

http://cran.r-project.org/web/views/Spatial.html

http://wiki.r-project.org/rwiki/doku.php?id=tips:spatial-data

http://wiki.r-project.org/rwiki/doku.php?id=tips:spatial-data


Spatial statistics with R

1 Introduction





6 Perspectives




Spatial statistic with R

R, GNU projet http://cran.r-project.org/

R. Bivand, E. Pebezma, V. Gomez-Rubio (2008), AppliedSpatial Data Analysis with R, Springer-Verlag.

R Spatial task viewhttp://cran.r-project.org/web/views/Spatial.html

Main packages for mapping : rgdal and maptools(import/export of spatial files, convert CRS/projection, etc),sp (definition of the Spatial classes and methods) and raster(for images).


http://cran.r-project.org/

http://cran.r-project.org/web/views/Spatial.html



Mapping with R

1 import the spatial file (.shp, .MIF, etc) intoR (readShapeFile, etc). There exists four main kind ofsptatial objects : points, polygons, lines, pixels.

2 eventually, change the CRS/projection

3 use the functions plot, points, legend, etc. for mapping.




Mapping with R : example

library(sp)

library(maptools)

xx = readShape-

Poly("NY8_utm18.shp",IDvar="AREAKEY",

CRS("+proj=utm +zone=18 +datum=WGS84"))

plot(xx,main="NY data",col=’blue3’)title("N-Y Leukemia Data")




Representation of SpatialPointsDataFrame andSpatialPolygonDataFrame objects

Soil Sample near the Meuse river

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Type of soil

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Core−periphery dummy

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Core−periphery / Income in Columbus OH

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Income

2.13.23.74.35.6




Representation of raster and PolyLines object

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Longitude (°)

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500−800 m800−1200 m

1200−1600 m

LTS Survey Tracks

VancouverIsland




Some advices

Which projection system ? Which reference system (veryimportant to give units to the distances) ?

Choice of palettes is important (see RColorBrewer package).

How find class intervals for continuous numerical variables :classInt package (“equal interval”,“quantile”,“K-means”, etc).

Interpolation can be useful to have a global view of spatialdistribution (variables, residuals, coefficients of GWR model,etc), see package akima.



Interactivity

1 Introduction





6 Perspectives



Interactivity

Package GeoXp

Package GeoXp : interactive spatial exploratory data analysis

may be download on http://cran.r-project.org.

a vignette : vignette("presentation_geoxp").

use the sp norm as defined by R. Bivand et al.

T. Laurent, A. Ruiz-Gazen et C. Thomas-Agnan(Forthcoming), “GeoXp : an R package for ExploratorySpatial Data Analysis”, JSS.

GeoXp, also available on Matlab


http://cran.r-project.org


Interactivity

Use of GeoXp

Arguments of a GeoXp function xxxmap (ex : histomap, barmap,densitymap, etc) :

a spatial object of class SpatialxxxDataFrame

the name of the studied variable(s) (univariate or multivariateanalysis)

options (colors, legend, etc.)

3 main kind of functions :

univariate analysis : histomap(columbus,"CRIME")

bivariate analysis :polyboxplotmap(columbus,c("CRIME","CP"))

spatial econometric function - spatial weight matrix(moranplotmap, neighbourmap, etc.)



Interactivity

GeoXp visual

A Tcl/Tk window, a map and a graphic



Application

1 Introduction





6 Perspectives



Application

Lorenz curve

data(mp.school)

coordinates(mp.school)<-cbind("longitude","latitude")ginimap(mp.school,"Nb.students")



Application

Variogramme

variocloudmap(mp.school,"Nb.students.per.class")



Application

Moran scatterplot of the number of students per class

coords <- coordinates(mp.school)

col.knn <- knn2nb(knearneigh(coords, k=4))moranplotmap(mp.school,"Nb.students.per.class",nb2listw(col.knn))

0 1

rurality.index

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FOIX

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TOULOUSEAUCH

TARBES

ALBIMONTAUBAN



Application

Drift map for the number of students per class

driftmap(mp.school,"Nb.students.per.class")

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Innovations of GeoXp

1 Introduction





6 Perspectives




Analysis of the spatial weight matrix

example(columbus)

histnbmap(columbus, col.gal.nb, criteria=(columbus$CP==1),xlab="distance of the neighbor the farest")




Analysis of outliers

Fothcoming

Pairwise spatial distances

Pai

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Conclusion and perspectives

1 Introduction





6 Perspectives




Having an interface such as GeoDa




Selecting directly the polygon such as a GIS or Arc Matlab




Manipulating directly the SGBD such as a GIS orArc Matlab




Other perspectives

Zoom on the device

Add origin-destination flow graphics

Mircromaps (Carr and Pickle)


geoxp: an r package for exploratory spatial data analysis ... · geoxp: an r package for...

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