Difference between revisions of "Lesson02"

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<br/>
  
Lesson 2: Geospatial Data Handling in R
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<font size ="6">'''Geospatial Data Handling in R'''</font>
  
 
=Content=
 
=Content=
 +
<font size ="4">'''Geospatial Data Handling in R'''
 
* Properties of geographical data
 
* Properties of geographical data
 
* Classes for geospatial data in R
 
* Classes for geospatial data in R
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=R Packages for Spatial Data Handling=
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=Lesson competencies=
  
Pebesma, Edzer. (2018) “Simple Features for R: Standardized Support for Spatial Vector Data.” ''The R Journal'', Vol. 10/1, 439:446. [https://journal.r-project.org/archive/2018/RJ-2018-009/RJ-2018-009.pdf]
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* Importing vector-based geospatial data such as shapefile, kml, etc into R using appropriate sf function(s).
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* Converting a simple feature data frame into spatial objection data frame of sp.
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* Importing raster-based geospatial data such as jpg into R using apporpriate raster function(s).
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* Performing georeferencing and spatial transformation using sf functions 
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* Performing vector-based geoprocessing function(s) using sf.
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* Performing raster-based map algebra and cartographic analysis using functions fro mraster package.
  
Pebesma, Z. (2018) "sf: Simple Features for R" [https://cran.r-project.org/web/packages/sf/index.html]
 
  
Pebesma, Edzer, and Roger Bivand. 2018. Sp: Classes and Methods for Spatial Data. [https://CRAN.R-project.org/package=sp]
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==Must do==
  
Bivand, Roger, Tim Keitt, and Barry Rowlingson. 2018. Rgdal: Bindings for the ’Geospatial’ Data Abstraction Library. [https://CRAN.R-project.org/package=rgdal]
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* Read Chapter 2, 3, 8, 9, 10 of Gimond, M. (2018) '''Intro to GIS and Spatial Analysis''' [https://mgimond.github.io/Spatial/index.html]
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* Complete the entire course of '''Spatial Analysis in R with sf and raster''' of Datacamp.
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* Complete Lesson 2: Point and polygon data, sub-topics on ''Introduction to sp objects'', ''sp and S4'', and ''More sp classes and methods'' of Datacamp course on '''Working with Geospatial Data in R'''.
  
Bivand, Roger, and Colin Rundel. 2018. Rgeos: Interface to Geometry Engine - Open Source (’Geos’). [https://CRAN.R-project.org/package=rgeos]
 
  
Maling, D. H. 1992. Coordinate Systems and Map Projections. 2nd ed. Oxford ; New York: Pergamon Press.
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=R Packages for Spatial Data Handling=
  
Pebesma, Edzer, Thomas Mailund, and James Hiebert. 2016. “Measurement Units in R.” The R Journal 8 (2): 486–94.
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Pebesma, Edzer. (2018) “Simple Features for R: Standardized Support for Spatial Vector Data.” ''The R Journal'', Vol. 10/1, 439:446. [https://journal.r-project.org/archive/2018/RJ-2018-009/RJ-2018-009.pdf]
  
 +
Pebesma, Z. (2018) '''sf: Simple Features for R''' [https://cran.r-project.org/web/packages/sf/index.html]
  
 +
Pebesma, Edzer, and Roger Bivand. 2018. '''sp: Classes and Methods for Spatial Data'''. [https://CRAN.R-project.org/package=sp]
  
 +
Bivand, Roger, Tim Keitt, and Barry Rowlingson. 2018. '''rgdal: Bindings for the ’Geospatial’ Data Abstraction Library'''. [https://CRAN.R-project.org/package=rgdal]
  
=Lesson competencies=
+
Bivand, Roger, and Colin Rundel. 2018. '''rgeos: Interface to Geometry Engine - Open Source (’Geos’)'''. [https://CRAN.R-project.org/package=rgeos]
 
 
=Technical References=
 
  
 +
Hijmans, R.J. (2018) '''raster: Geographic Data Analysis and Modeling''' [https://cran.r-project.org/web/packages/raster/index.html]
  
=Application References=
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</font>

Latest revision as of 07:45, 14 January 2019

Claraview.png IS415 GeoSpatial Analytics and Applications

About

Weekly Session

Take-home Exercises

Geospatial Analytics Project

Course Resources

 


Geospatial Data Handling in R

Content

Geospatial Data Handling in R

  • Properties of geographical data
  • Classes for geospatial data in R
  • Simple features data in R
  • Georeferencing
  • Using R as a GIS


Lesson competencies

  • Importing vector-based geospatial data such as shapefile, kml, etc into R using appropriate sf function(s).
  • Converting a simple feature data frame into spatial objection data frame of sp.
  • Importing raster-based geospatial data such as jpg into R using apporpriate raster function(s).
  • Performing georeferencing and spatial transformation using sf functions
  • Performing vector-based geoprocessing function(s) using sf.
  • Performing raster-based map algebra and cartographic analysis using functions fro mraster package.


Must do

  • Read Chapter 2, 3, 8, 9, 10 of Gimond, M. (2018) Intro to GIS and Spatial Analysis [1]
  • Complete the entire course of Spatial Analysis in R with sf and raster of Datacamp.
  • Complete Lesson 2: Point and polygon data, sub-topics on Introduction to sp objects, sp and S4, and More sp classes and methods of Datacamp course on Working with Geospatial Data in R.


R Packages for Spatial Data Handling

Pebesma, Edzer. (2018) “Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal, Vol. 10/1, 439:446. [2]

Pebesma, Z. (2018) sf: Simple Features for R [3]

Pebesma, Edzer, and Roger Bivand. 2018. sp: Classes and Methods for Spatial Data. [4]

Bivand, Roger, Tim Keitt, and Barry Rowlingson. 2018. rgdal: Bindings for the ’Geospatial’ Data Abstraction Library. [5]

Bivand, Roger, and Colin Rundel. 2018. rgeos: Interface to Geometry Engine - Open Source (’Geos’). [6]

Hijmans, R.J. (2018) raster: Geographic Data Analysis and Modeling [7]