Difference between revisions of "Lesson02"
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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 |
| − | * | + | * Classes for geospatial data in R |
| − | * | + | * Simple features data in R |
| − | * GIS | + | * Georeferencing |
| + | * Using R as a GIS | ||
=Lesson competencies= | =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''' [https://mgimond.github.io/Spatial/index.html] | ||
| + | * 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. [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] | ||
| + | |||
| + | 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] | ||
| − | + | </font> | |
Latest revision as of 07:45, 14 January 2019
IS415 GeoSpatial Analytics and Applications
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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]
