Difference between revisions of "Lesson02"

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<br/>
 
<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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* Georeferencing
 
* Georeferencing
 
* Using R as a GIS
 
* Using R as a GIS
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 +
 +
=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.
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* 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.
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* Performing raster-based map algebra and cartographic analysis using functions fro mraster package.
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 +
 +
==Must do==
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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'''.
  
  
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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, 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]
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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]
 
Pebesma, Edzer, and Roger Bivand. 2018. '''sp: Classes and Methods for Spatial Data'''. [https://CRAN.R-project.org/package=sp]
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Bivand, Roger, and Colin Rundel. 2018. '''rgeos: Interface to Geometry Engine - Open Source (’Geos’)'''. [https://CRAN.R-project.org/package=rgeos]
 
Bivand, Roger, and Colin Rundel. 2018. '''rgeos: Interface to Geometry Engine - Open Source (’Geos’)'''. [https://CRAN.R-project.org/package=rgeos]
  
Hijmans, R.J. (2018) '''raster: Geographic Data Analysis and Modeling''' [https://cran.r-project.org/web/packages/raster/index.html]  
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Hijmans, R.J. (2018) '''raster: Geographic Data Analysis and Modeling''' [https://cran.r-project.org/web/packages/raster/index.html]
 
 
 
 
 
 
=Lesson competencies=
 
 
 
=Technical References=
 
Maling, D. H. 1992. Coordinate Systems and Map Projections. 2nd ed. Oxford ; New York: Pergamon Press.
 
 
 
  
=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]