View
4.602
Download
3
Category
Preview:
DESCRIPTION
The following presentation contains some basic introduction materials for R beginners.
Citation preview
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
R crash course(for people who pick up new methods/tools quickly
and have a high motivation to learn)
T. Hengl1 & R.S. Bivand2
1Instituut voor Biodiversiteit en Ecosysteem DynamicaUniversiteit van Amsterdam
2Department of EconomicsNorwegian School of Economics and Business administration
June 19, 2010
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Programme
Installation and first (baby) steps (intro.R).
Building, running and editing models in R.
Working with spatial data.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Crash course
A “crash course” is a compressed version of a training course forpeople that already have full agendas. It is really intended for
people who pick up new methods/tools quickly and have a highmotivation to learn (PhD students?). This means no longquestions, no going back, no long discussion, no complains
about the speed/programme of the course. . . and of course: nopromises that you will manage to learn R in such a short time.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
The course programme
Basic concepts (self-study)
R basic and add-on packages;
R syntax; R objects and ’methods’;
R FAQs; getting help and the most important literature;
Scripting in R
data management; creating and debugging scripts(scripting editors: Tinn-R);
automating analysis — making functions and packages;
publication quality outputs (using R+Sweave);
Advanced topics
GDAL and R; spatial classes and packages;
calling external applications from R (SAGA GIS, FWTools,Python, Matlab;
export of maps to Google Earth;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Getting the right motivation (inspiration)
What is R, and why should you invest time to learn it?
What can it do? (and what it can’t do?)
How does the R community works (what are its sharedprinciples)?
Is R suited for spatio-temporal data analysis?
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Some important assumptions
R is (increasingly) sexy.
R is hell.
You are all beginners (who need a gentle intro).
You are non-statisticians / computer scientists.
I learned R myself. If I can do it, you can do it too.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Some important assumptions
R is (increasingly) sexy.
R is hell.
You are all beginners (who need a gentle intro).
You are non-statisticians / computer scientists.
I learned R myself. If I can do it, you can do it too.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Some important assumptions
R is (increasingly) sexy.
R is hell.
You are all beginners (who need a gentle intro).
You are non-statisticians / computer scientists.
I learned R myself. If I can do it, you can do it too.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Some important assumptions
R is (increasingly) sexy.
R is hell.
You are all beginners (who need a gentle intro).
You are non-statisticians / computer scientists.
I learned R myself. If I can do it, you can do it too.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Some important assumptions
R is (increasingly) sexy.
R is hell.
You are all beginners (who need a gentle intro).
You are non-statisticians / computer scientists.
I learned R myself. If I can do it, you can do it too.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What is R?
the open source implementation of the S language forstatistical computing created by created by Ross Ihakaand Robert Gentleman (now maintained by the RDevelopment Core Team);
why R?: the name “R” was selected for two reasons: (1)precedence —“R”is a letter before“S”, and (2) coincidence— both of the creators’ names start with a letter “R”;
it is a computer language developed to simplify statisticalcomputing/programming;
it offers many contributed packages, technical documents,demos and examples;
widely recognized as one of the fastest growing and mostcomprehensive statistical computing tools;
it is a movement;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What is R?
the open source implementation of the S language forstatistical computing created by created by Ross Ihakaand Robert Gentleman (now maintained by the RDevelopment Core Team);
why R?: the name “R” was selected for two reasons: (1)precedence —“R”is a letter before“S”, and (2) coincidence— both of the creators’ names start with a letter “R”;
it is a computer language developed to simplify statisticalcomputing/programming;
it offers many contributed packages, technical documents,demos and examples;
widely recognized as one of the fastest growing and mostcomprehensive statistical computing tools;
it is a movement;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What is R?
the open source implementation of the S language forstatistical computing created by created by Ross Ihakaand Robert Gentleman (now maintained by the RDevelopment Core Team);
why R?: the name “R” was selected for two reasons: (1)precedence —“R”is a letter before“S”, and (2) coincidence— both of the creators’ names start with a letter “R”;
it is a computer language developed to simplify statisticalcomputing/programming;
it offers many contributed packages, technical documents,demos and examples;
widely recognized as one of the fastest growing and mostcomprehensive statistical computing tools;
it is a movement;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What is R?
the open source implementation of the S language forstatistical computing created by created by Ross Ihakaand Robert Gentleman (now maintained by the RDevelopment Core Team);
why R?: the name “R” was selected for two reasons: (1)precedence —“R”is a letter before“S”, and (2) coincidence— both of the creators’ names start with a letter “R”;
it is a computer language developed to simplify statisticalcomputing/programming;
it offers many contributed packages, technical documents,demos and examples;
widely recognized as one of the fastest growing and mostcomprehensive statistical computing tools;
it is a movement;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What is R?
the open source implementation of the S language forstatistical computing created by created by Ross Ihakaand Robert Gentleman (now maintained by the RDevelopment Core Team);
why R?: the name “R” was selected for two reasons: (1)precedence —“R”is a letter before“S”, and (2) coincidence— both of the creators’ names start with a letter “R”;
it is a computer language developed to simplify statisticalcomputing/programming;
it offers many contributed packages, technical documents,demos and examples;
widely recognized as one of the fastest growing and mostcomprehensive statistical computing tools;
it is a movement;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What is R?
the open source implementation of the S language forstatistical computing created by created by Ross Ihakaand Robert Gentleman (now maintained by the RDevelopment Core Team);
why R?: the name “R” was selected for two reasons: (1)precedence —“R”is a letter before“S”, and (2) coincidence— both of the creators’ names start with a letter “R”;
it is a computer language developed to simplify statisticalcomputing/programming;
it offers many contributed packages, technical documents,demos and examples;
widely recognized as one of the fastest growing and mostcomprehensive statistical computing tools;
it is a movement;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
R is “sexy”
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Quote
“R has really become the second language for peoplecoming out of grad school now, and there’s anamazing amount of code being written for it.”
Max Kuhn
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What it is NOT
it’s not a software with GUI and point-and-click control;
there are practically no data analysis wizards;
it’s not an interactive system;
it comes with no warranties (but so does the commercialsoftware too!!);
there is practically no formal support;
however. . .
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What it is NOT
it’s not a software with GUI and point-and-click control;
there are practically no data analysis wizards;
it’s not an interactive system;
it comes with no warranties (but so does the commercialsoftware too!!);
there is practically no formal support;
however. . .
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What it is NOT
it’s not a software with GUI and point-and-click control;
there are practically no data analysis wizards;
it’s not an interactive system;
it comes with no warranties (but so does the commercialsoftware too!!);
there is practically no formal support;
however. . .
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What it is NOT
it’s not a software with GUI and point-and-click control;
there are practically no data analysis wizards;
it’s not an interactive system;
it comes with no warranties (but so does the commercialsoftware too!!);
there is practically no formal support;
however. . .
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What it is NOT
it’s not a software with GUI and point-and-click control;
there are practically no data analysis wizards;
it’s not an interactive system;
it comes with no warranties (but so does the commercialsoftware too!!);
there is practically no formal support;
however. . .
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
What it is NOT
it’s not a software with GUI and point-and-click control;
there are practically no data analysis wizards;
it’s not an interactive system;
it comes with no warranties (but so does the commercialsoftware too!!);
there is practically no formal support;
however. . .
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Why make scripts?
It’s easy to use: “Because S (and its implementation R) isa well-developed, simple and effective programminglanguage which includes conditionals, loops, user-definedrecursive functions and input and output facilities, existingfunctions can be modified.” In R we all becomeprogrammers (but much faster than with C++ or Java).
The basic approach to using R is to generate scripts thatdefine the data processing steps (workflows?).
Documenting the analysis process is a “good thing”, soprogramming scripts are not just a burden, certainly forusers doing original research and repetitive work, arguablyfor student classes too.
Point-and-click operations are for amateurs.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Why make scripts?
It’s easy to use: “Because S (and its implementation R) isa well-developed, simple and effective programminglanguage which includes conditionals, loops, user-definedrecursive functions and input and output facilities, existingfunctions can be modified.” In R we all becomeprogrammers (but much faster than with C++ or Java).
The basic approach to using R is to generate scripts thatdefine the data processing steps (workflows?).
Documenting the analysis process is a “good thing”, soprogramming scripts are not just a burden, certainly forusers doing original research and repetitive work, arguablyfor student classes too.
Point-and-click operations are for amateurs.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Why make scripts?
It’s easy to use: “Because S (and its implementation R) isa well-developed, simple and effective programminglanguage which includes conditionals, loops, user-definedrecursive functions and input and output facilities, existingfunctions can be modified.” In R we all becomeprogrammers (but much faster than with C++ or Java).
The basic approach to using R is to generate scripts thatdefine the data processing steps (workflows?).
Documenting the analysis process is a “good thing”, soprogramming scripts are not just a burden, certainly forusers doing original research and repetitive work, arguablyfor student classes too.
Point-and-click operations are for amateurs.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Why make scripts?
It’s easy to use: “Because S (and its implementation R) isa well-developed, simple and effective programminglanguage which includes conditionals, loops, user-definedrecursive functions and input and output facilities, existingfunctions can be modified.” In R we all becomeprogrammers (but much faster than with C++ or Java).
The basic approach to using R is to generate scripts thatdefine the data processing steps (workflows?).
Documenting the analysis process is a “good thing”, soprogramming scripts are not just a burden, certainly forusers doing original research and repetitive work, arguablyfor student classes too.
Point-and-click operations are for amateurs.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Do you speak R?
After some time you basically discovered that most of the thingsyou want to do, you can do in R, the only question is how.
Well, first, you have to learn to how to speak’n’write R.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Why NOT Matlab?
R and Matlab are in fact very similar, except. . . :
(almost) everything you do in Matlab, you can do in R;
R can be used to write homework (for Matlab you need acomputer lab with software licences);
“R gradually pushes people towards better programminghabits” (Tamas K. Papp);
Matlab has a limited support for processing spatial data (Ris better);
Contributed packages in R are growing faster (R is better);
We are in academia — we shouldn’t be developingtoolboxes for some private company but for the people(and for ourselves);
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
A bit of history
R was first time released in 1997;
majority of the development is (still) done by prof. BrianD. Ripley;
a the moment (juni 19 2010 10:01), there are 2387contributed packages!
according to Google trends, R-project.org has acommunity of about 200–350k active users;
in 2003, a group of researchers (International Workshop onDistributed Statistical Computing) decided to add Spatialfunctionality to R;
. . . now is time to use it more broadly (MSc level and PhDlevel modules, projects, reports and scientific documents);
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Quote
“Once methodological problems start being perceivedor even defined in terms of what one’s favoritesoftware does well, then the software has stoppedbeing a tool, and has become a crutch, and at worse ashackle.”
Simon Jackman
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
The ASDA(R)-book.org
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
The ASDA(R) team
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
A Practical Guide to Geostatistical Mapping
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Quote
“I created Quick-R for one simple reason. I wanted tolearn R and I am a teacher at heart. The easiest wayfor me to learn something is to teach it”
Robert I. Kabacoff
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Software
Not all software is required to follow the exercises
R v2.11 (Windows OS) including a list of packages;
Tinn-R v2.3 (code editor);
Optional: FWTools v2.4 — a list of utilities to handlespatial data; SAGA GIS v2.0.4 — a light GIS excellent foreducational purposes.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Installing the add-on packages
> install.packages("ctv")
> library(ctv)
> install.views("Spatial")
This will install all connected packages listed at R views Spatial.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Check your installation
> Sys.getenv(c("OS", "COMPUTERNAME", "R_HOME", "R_LIBS_USER",
+ "PROCESSOR_IDENTIFIER"))
OS
"Windows_NT"
COMPUTERNAME
"PC-IBED193"
R_HOME
"C:\\PROGRA~1\\R\\R-210~1.1"
R_LIBS_USER
"n:/R/win-library/2.10"
PROCESSOR_IDENTIFIER
"x86 Family 6 Model 15 Stepping 6, GenuineIntel"
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Making friends with R
1 Use script editors such as as TINN-R or JGR (syntaxhighlighting, wrapping, search/replace etc.).
2 The best way to learn R is to look at the existing scripts,then extend:
Graphical Manual/Addicted to R — if you prefer to exploreexamples graphically;Teach-your-self books e.g. “Statistics with R” or “AnIntroduction to R”; “Introduction to R for ITC students”Quick-R and/or R by example;
3 If your R script does not work, do not break your head, tryto get help:
local installation: > help.search("kriging");R-project: > RSiteSearch("krige dimensions do notmatch")www: Rseek.orgR mailing lists;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Good practice
Put comments in script (after #).
Add some meta-information at the beginning of yourscript.
Once you tested your script and saw that it works, tidy-upthe code.
Place the input data on-line (database) so you cancommunicate only the script.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
R mailing lists: Do’s and Don’ts!
Do’s:
If you have not done so already, read the R posting guide.Use the existing pre-installed data sets (come together witha certain package) to describe your problem; link yourproblem to some existing problems.Acknowledge the work (time spent) other people do to helpyou.You can submit not only the problems you discover but alsothe information that you think is interesting for thecommunity.
Don’ts:
Do not send poorly formulated questions.Do not send too much.Complaining to a mailing list about what frustrates youabout R makes no sense.You are requesting that somebody does a work for you thatyou could do yourself!
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Tinn-R
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
JaGuaR
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Spatial objects
An advantage of R (as compared to e.g. Matlab) is that youcan create your own formats and structures for data. But ifthere are too many formats you can easily get lots. In addition,we want to have smooth links to external formats (R is open!).
To reduce this problem, Bivand et al. (2008) developednew-style classes to represent spatial data.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Spatial class
The foundation object is the Spatial class, with just two basicslots (new-style S classes have pre-defined components calledslots):
a bounding box — mostly used for setting up plots;
a CRS class object — defining the coordinate referencesystem, and may be set to CRS(as.character(NA));
Operations on Spatial* objects should update or copy thesevalues to the new Spatial* objects being created. The mostbasic spatial data object is a point, which may have 2 or 3dimensions.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Spatial classes
for point features: SpatialPoints;SpatialPointsDataFrame;
for line features: SpatialLines,SpatialLinesDataFrame;
polygons: SpatialPolygons,SpatialPolygonsDataFrame;
rasters: SpatialPixels, SpatialPixelsDataFrame,SpatialGrid, SpatialGridDataFrame;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
SpatialPoints
> library(sp)
> data(meuse)
> coords <- SpatialPoints(meuse[, c("x", "y")])
> summary(coords)
Object of class SpatialPoints
Coordinates:
min max
x 178605 181390
y 329714 333611
Is projected: NA
proj4string : [NA]
Number of points: 155
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
SpatialPointsDataFrame
We can add the tabular data to make aSpatialPointsDataFrame object:
> meuse1 <- SpatialPointsDataFrame(coords, meuse)
> str(meuse1, max.level = 2)
Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots
..@ data :'data.frame': 155 obs. of 14 variables:
..@ coords.nrs : num(0)
..@ coords : num [1:155, 1:2] 181072 181025 181165 ...
.. ..- attr(*, "dimnames")=List of 2
..@ bbox : num [1:2, 1:2] 178605 329714 181390 333611
.. ..- attr(*, "dimnames")=List of 2
..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slots
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Point features
Spatial points
Using the Meuse bank data set of soil samples and measurementsof heavy metal pollution provided with sp, we’ll make aSpatialPoints object.> library(sp)
> data(meuse)
> coords <- SpatialPoints(meuse[, c("x", "y")])
> summary(coords)
Object of class SpatialPoints
Coordinates:
min max
x 178605 181390
y 329714 333611
Is projected: NA
proj4string : [NA]
Number of points: 155
Spatial points
Now we’ll add the original data frame to make aSpatialPointsDataFrame object. Many methods for standard dataframes just work with SpatialPointsDataFrame objects.> meuse1 <- SpatialPointsDataFrame(coords, meuse)
> names(meuse1)
[1] "x" "y" "cadmium" "copper" "lead" "zinc"
[7] "elev" "dist" "om" "ffreq" "soil" "lime"
[13] "landuse" "dist.m"
> summary(meuse1$zinc)
Min. 1st Qu. Median Mean 3rd Qu. Max.
113.0 198.0 326.0 469.7 674.5 1839.0
> stem(meuse1$zinc, scale = 1/2)
The decimal point is 2 digit(s) to the right of the |
0 | 12223333344444455666677778888899999999
2 | 000000011111112222233444555666678880022334455788
4 | 00012235677001455556789
6 | 01144678890012455678889
8 | 0133113
10 | 235604469
12 | 8
14 | 5357
16 | 7
18 | 4
Spatial points classes and their slots
coordsSpatial
coords.nrsdata
SpatialPoints bboxproj4string
SpatialPointsDataFrame
data.frame
Spatial
SpatialPoints
Spatial lines and polygons
I A Line object is just a spaghetti collection of 2D coordinates;a Polygon object is a Line object with equal first and lastcoordinates
I A Lines object is a list of Line objects, such as all thecontours at a single elevation; the same relationship holdsbetween a Polygons object and a list of Polygon objects, suchas islands belonging to the same county
I SpatialLines and SpatialPolygons objects are made usinglists of Lines or Polygons objects respectively
I SpatialLinesDataFrame and SpatialPolygonsDataFrame
objects are defined using SpatialLines and SpatialPolygons
objects and standard data frames, and the ID fields are hererequired to match the data frame row names
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Line/polygon featuresSpatial polygons
The Meuse bank data set also includes the coordinates of the edgeof the river, linked together at the edge of the study area to form apolygon. We can make these coordinates into a SpatialPolygons
object:> data(meuse.riv)
> str(meuse.riv)
num [1:176, 1:2] 182004 182137 182252 182314 182332 ...
> river_polygon <- Polygons(list(Polygon(meuse.riv)), ID = "meuse")
> rivers <- SpatialPolygons(list(river_polygon))
> summary(rivers)
Object of class SpatialPolygons
Coordinates:
min max
r1 178304.0 182331.5
r2 325698.5 337684.8
Is projected: NA
proj4string : [NA]
Spatial linesThere is a helper function contourLines2SLDF to convert the list ofcontours returned by contourLines into a SpatialLinesDataFrame
object. This example shows how the data slot row names matchthe ID slot values of the set of Lines objects making up theSpatialLinesDataFrame, note that some Lines objects includemultiple Line objects:> library(maptools)
> volcano_sl <- ContourLines2SLDF(contourLines(volcano))
> row.names(slot(volcano_sl, "data"))
[1] "C_1" "C_2" "C_3" "C_4" "C_5" "C_6" "C_7" "C_8" "C_9"
[10] "C_10"
> sapply(slot(volcano_sl, "lines"), function(x) slot(x,
+ "ID"))
[1] "C_1" "C_2" "C_3" "C_4" "C_5" "C_6" "C_7" "C_8" "C_9"
[10] "C_10"
> sapply(slot(volcano_sl, "lines"), function(x) length(slot(x,
+ "Lines")))
[1] 3 4 1 1 1 2 2 3 2 1
> volcano_sl$level
[1] 100 110 120 130 140 150 160 170 180 190
Levels: 100 110 120 130 140 150 160 170 180 190
Spatial Polygons classes and slots
coordsSpatiallines
plotOrderSpatial
polygons
bboxproj4string
Polygon
coords
labptareaholeringDir
LineLines
ID
Polygons
plotOrderlabptIDarea
SpatialLines
Spatial
SpatialPolygons
Lines
Polygons
Spatial grids and pixels
I There are two representations for data on regular rectangulargrids (oriented N-S, E-W): SpatialPixels and SpatialGrid
I SpatialPixels are like SpatialPoints objects, but thecoordinates have to be regularly spaced; the coordinates arestored, as are grid indices
I SpatialPixelsDataFrame objects only store attribute datawhere it is present, but need to store the coordinates and gridindices of those grid cells
I SpatialGridDataFrame objects do not need to storecoordinates, because they fill the entire defined grid, but theyneed to store NA values where attribute values are missing
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Grids
Spatial pixels
Let’s make a SpatialPixelsDataFrame object for the Meuse bankgrid data provided, with regular points at a 40m spacing. The datainclude soil types, flood frequency classes and distance from theriver bank:> data(meuse.grid)
> coords <- SpatialPixels(SpatialPoints(meuse.grid[, c("x",
+ "y")]))
> meuseg1 <- SpatialPixelsDataFrame(coords, meuse.grid)
> names(meuseg1)
[1] "x" "y" "part.a" "part.b" "dist" "soil" "ffreq"
> slot(meuseg1, "grid")
x y
cellcentre.offset 178460 329620
cellsize 40 40
cells.dim 78 104
> object.size(meuseg1)
[1] 339036
> dim(slot(meuseg1, "data"))
[1] 3103 7
Spatial grids
In this case we convert the SpatialPixelsDataFrame object to aSpatialGridDataFrame by making a change in-place. In othercontexts, it is much more usual to create the GridTopology objectin the grid slot directly, and populate the grid from there, as we’llsee later:> meuseg2 <- meuseg1
> fullgrid(meuseg2) <- TRUE
> slot(meuseg2, "grid")
x y
cellcentre.offset 178460 329620
cellsize 40 40
cells.dim 78 104
> class(slot(meuseg2, "grid"))
[1] "GridTopology"
attr(,"package")
[1] "sp"
> object.size(meuseg2)
[1] 425684
> dim(slot(meuseg2, "data"))
[1] 8112 7
Spatial grid and pixels classes and their slots
dataSpatialPixels
SpatialGriddata grid
grid.indexSpatialPoints
gridgrid.indexSpatialPoints
cellcentre.offsetcellsizecells.dim
coordsSpatial
bboxproj4string
data.frame
Spatial
GridTopology
SpatialPoints
SpatialGridDataFrameSpatialGrid
SpatialPixelsSpatialPixelsDataFrame
Spatial classes provided by sp
This table summarises the classes provided by sp, and shows howthey build up to the objects of most practical use, theSpatial*DataFrame family objects:
data type class attributes extendspoints SpatialPoints none Spatial
points SpatialPointsDataFrame data.frame SpatialPoints
pixels SpatialPixels none SpatialPoints
pixels SpatialPixelsDataFrame data.frame SpatialPixels
SpatialPointsDataFrame
full grid SpatialGrid none SpatialPixels
full grid SpatialGridDataFrame data.frame SpatialGrid
line Line nonelines Lines none Line listlines SpatialLines none Spatial, Lines listlines SpatialLinesDataFrame data.frame SpatialLines
polygon Polygon none Line
polygons Polygons none Polygon listpolygons SpatialPolygons none Spatial, Polygons listpolygons SpatialPolygonsDataFrame data.frame SpatialPolygons
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Basic methods
spplot — plotting of spatial objects (maps);
spsample — sample points from a set of polygons, on aset of lines or from a gridded area;
bbox — get the bounding box;
proj4string — get or set the projection (coordinatereference system);
coordinates — set or retrieve coordinates;
spTransform — transform coordinates from one CRS toanother;
overlay — combine two different spatial objects;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Plotting a SpatialPoints object
> plot(as(meuse1, "Spatial"), axes = TRUE)
> plot(meuse1, add = TRUE)
> plot(meuse1[meuse1$ffreq == 1, ], col = "green", add = TRUE)
178000 179000 180000 181000 182000
3300
0033
1000
3320
0033
3000
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Combining statistical and GIS operations
Because the Spatial*DataFrame family objects behave inmost cases like data frames, most of what we are used todoing with standard data frames just works (but no merge,etc., yet).
These objects are very similar to typical representations ofthe same kinds of objects in geographical informationsystems, so they do not suit spatial data that is notgeographical (like medical imaging) as such.
Because now sp classes for GIS data exits, this opens thedoor for fusing GIS and statistical operations (this has notbeen possible in e.g. 2002).
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Spatial packages
R now offers a range of contributed packages in spatialstatistics and increasing awareness of the importance of spatialdata analysis in the broader community. Current contributedpackages with spatial applications:
point patterns: spatstat, VR:spatial, splancs;
geostatistics: gstat, geoR, geoRglm, fields, spBayes,RandomFields, VR:spatial, sgeostat, vardiag;
lattice/area data: spdep, DCluster, spgwr, ade4;
links to GIS: rgdal, spgrass, RPy, RSAGA;
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Let’s create spatial objects!
We can create spatial objects from scratch! For example aDEM:
> dem <- expand.grid(x = seq(100, 600, 100), y = seq(100,
+ 600, 100))
> dem$Z <- as.vector(c(23, 24, 34, 38, 45, 51, 24, 20,
+ 20, 28, 18, 49, 22, 20, 19, 14, 38, 45, 19, 15, 13,
+ 21, 23, 25, 14, 11, 18, 11, 18, 19, 10, 16, 23, 16,
+ 9, 6))
> gridded(dem) <- ~x + y
> dem <- as(dem, "SpatialGridDataFrame")
> str(dem)
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
A small DEM
> dem.plt <- spplot(dem[1], main = "DEM", scales = list(draw = FALSE),
+ col.regions = topo.colors(25))
> print(dem.plt)
> writeGDAL(dem, "dem6.sdat", "SAGA")
DEM
10
20
30
40
50
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Controlling SAGA from R
> library(RSAGA)
> rsaga.env()
$workspace
[1] "."
$cmd
[1] "saga_cmd.exe"
$path
[1] "C:/PROGRA~1/R/R-210~1.1/library/RSAGA/saga_vc"
$modules
[1] "C:/PROGRA~1/R/R-210~1.1/library/RSAGA/saga_vc/modules"
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Getting list of modules
> rsaga.get.modules("ta_channels")
$ta_channels
code name interactive
1 0 Channel Network FALSE
2 1 Watershed Basins FALSE
3 2 Watershed Basins (extended) FALSE
4 3 Vertical Distance to Channel Network FALSE
5 4 Overland Flow Distance to Channel Network FALSE
6 5 D8 Flow Analysis FALSE
7 6 Strahler Order FALSE
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Run stream extraction
> rsaga.geoprocessor(lib = "ta_channels", module = 5, param = list(DEM = "dem6.sgrd",
+ DIRECTION = "channels.sgrd", CONNECTION = "route.sgrd",
+ NETWORK = "channels.shp"))
SAGA CMD 2.0.4
library path: C:/PROGRA~1/R/R-210~1.1/library/RSAGA/...
library name: ta_channels
module name : D8 Flow Analysis
author : (c) 2003 by O.Conrad
Load grid: dem6.sgrd...
ready
Parameters
Grid system: 100; 6x 6y; 100x 100y
DEM: dem6
Flow Direction: Flow Direction
Flow Connectivity: Flow Connectivity
Flow Network: Flow Network
Minimum Connectivity: 0
...
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Read back to R
> dem$route <- readGDAL("route.sdat")$band1
route.sdat has GDAL driver SAGA
and has 6 rows and 6 columns
> channels <- readOGR("channels.shp", "channels")
OGR data source with driver: ESRI Shapefile
Source: "channels.shp", layer: "channels"
with 32 features and 2 fields
Feature type: wkbLineString with 2 dimensions
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Plot the final result
> dem.plt <- spplot(dem[1], main = "DEM", col.regions = topo.colors(25))
> channels.plt <- spplot(dem[2], col.regions = rev(gray(0:20/20)),
+ main = "Flow connectivity", sp.layout = list("sp.lines",
+ channels, col = "red"))
> print(dem.plt, split = c(1, 1, 2, 1), more = T)
> print(channels.plt, split = c(2, 1, 2, 1), more = F)
DEM
10
20
30
40
50
Flow connectivity
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Preparing FWTools
There is still no package to control FWTools from R, but we cansimply send command lines using the system command. Beforewe can use FWTools from R, we need to locate it on our PC:
> gdalwarp <- gsub("/", "\\\\", dir(path="C:/PROGRA~2/FWTOOL~1.7",
+ pattern="gdalwarp.exe", recursive=TRUE, full.names=TRUE))
> gdalwarp
[1] "C:\\PROGRA~2\\FWTOOL~1.7\\bin\\gdalwarp.exe"
> workd <- paste(gsub("/", "\\\\", getwd()), "\\", sep="")
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
MODIS data
Now we can download some GIS data from web:
> MOD12Q1 <- "ftp://anonymous:test@e4ftl01u.ecs.nasa.gov/
+ MOLT/MOD12Q1.004/2004.01.01/"
> download.file(paste(MOD12Q1,
+ "MOD12Q1.A2004001.h18v03.004.2006117173748.hdf", sep=""),
+ destfile=paste(getwd(),
+ "MOD12Q1.A2004001.h18v03.004.2006117173748.hdf", sep="/"),
+ mode='wb', method='wget')
Resolving e4ftl01u.ecs.nasa.gov... 152.61.4.83
Connecting to e4ftl01u.ecs.nasa.gov|152.61.4.83|:21... connected.
Logging in as anonymous ... Logged in!
==> SYST ... done. ==> PWD ... done.
==> TYPE I ... done. ==> CWD /MOLT/MOD12Q1.004/2004.01.01 ... done.
==> SIZE MOD12Q1.A2004001.h18v03.004.2006117173748.hdf ... 23165983
==> PASV ... done. ==> RETR MOD12Q1.A2004... done.
Length: 23165983 (22M)
0K .......... .......... 0% 64.9K 5m48s
...
22550K .......... .......... 99% 501K 0s
22600K .......... 100% 503K=65s
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Reprojecting grids
We can reproject/resample the map to our local coordinatesystem using the gdalwarp functionality (this combines severalprocessing steps in one function):
> NL.prj <- "+proj=sterea +lat_0=52.15616055555555
+ +lon_0=5.38763888888889 +k=0.999908 +x_0=155000
+ +y_0=463000 +ellps=bessel +units=m +no_defs
+ +towgs84=565.237,50.0087,465.658,
+ -0.406857,0.350733,-1.87035,4.0812"
> system(paste(gdalwarp, " HDF4_EOS:EOS_GRID:\"", workd,
+ "\\MOD12Q1.A2004001.h18v03.004.2006117173748.hdf\"
+ :MOD12Q1:Land_Cover_Type_1 -t_srs \"", NL.prj, "\"
+ IGBP2004NL.tif -r near -te 0 300000 280000 625000
+ -tr 500 500", sep=""))
Creating output file that is 560P x 650L.
Processing input file HDF4_EOS:EOS_GRID:\\MOD12Q1.A2004001...
Using internal nodata values (eg. 255) for image HDF4_EOS:EOS_...
0...10...20...30...40...50...60...70...80...90...100 - done.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Plot the final result
In this case we have produced a MODIS-based land cover mapfor the whole Netherlands in resolution of 500 m (in localcoordinate system).
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Outline
1 OverviewCourse programmeWhy R?Software installation
2 Scripting in RDo’s and don’tsR code editors
3 Working with spatial dataSpatial classesSpatial methodsR+SAGAR+FWToolsExport to Google Earth
4 Literature
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Writing spatial data to KML
There are two possibilities to export maps to KML: (a)using existing packages, and (b) by writing KML files“by-hand”.
To export point or line features to KML, use the writeOGRmethod that is available in R package rgdal.
More flexible way to writing KML files is by using loops.
R crashcourse
T. Hengl &R.S. Bivand
Overview
Course programme
Why R?
Software installation
Scripting in R
Do’s and don’ts
R code editors
Working withspatial data
Spatial classes
Spatial methods
R+SAGA
R+FWTools
Export to GoogleEarth
Literature
Literature
Bivand, R., Pebesma, E., Rubio, V., 2008. Applied SpatialData Analysis with R. Use R Series, Springer, Heidelberg,378 p.
Hengl, T., 2009. A Practical Guide to GeostatisticalMapping, 2nd edition. University of Amsterdam, 291 p.ISBN 978-90-9024981-0.
Kabacoff, R.I., 2009. Data Analysis and Graphics with R.Manning publications, 375 p.
Zuur, A. F., Ieno, E. N., Meesters, E. H. W. G., 2009. ABeginner’s Guide to R. Springer, Use R series, 228 p.
Recommended