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- Welcome to Mapping with R (01_01)
-
Geospatial Data
- Making Maps is Complex (01_02)
- mapview for Quick Maps (01_03)
- sf for Simple Features (01_04)
- Turning Data Frames into sf Objects (01_05)
- Importing Shapefiles (01_06)
- Joining Geospatial Datasets (01_07)
- Disambiguating Country Names (01_08)
- Converting Addresses to Coordinates (01_09)
- U.S.-Specific Datasets (01_10)
- Advice on Finding International Datasets (01_11)
- CRS and Projections: Geographic and Projected CRS (01_12)
- CRS and Projections: How to Choose a CRS (01_13)
- Introducing Raster GIS with raster and stars (01_14)
- Basics of Using the raster Package (01_15)
-
Static Maps
- ggplot2 Essentials (02_01)
- Starting a Map in ggplot2 (02_02)
- Labelling ggplot2 Maps (02_03)
- Compare Locations/Events with Geobubble Charts (02_04)
- Highlight a Region in a Country with ggplot2 (02_05)
- Make a Choropleth Map of Discrete Variables with ggplot2 (02_06)
- Make a Choropleth Map of Continuous Variables with ggplot2 (02_07)
- Faceting Choropleth Maps with ggplot2 (02_08)
- Visualize Raster Data with ggplot2 (02_09)
- Adding Scale Bars and North Arrows with ggplot2 (02_10)
-
Interactive Maps
- What is leaflet? (03_01)
- Starting a Map in leaflet (03_02)
- Necessary HTML for Labelling leaflet Maps (03_03)
- Highlight a Region in a Country with leaflet (03_04)
- Compare Locations/Events with Geobubble Charts in leaflet (03_05)
- Make a Choropleth Map of Discrete Variables with leaflet (03_06)
- Make a Choropleth Map of Continuous Variables with leaflet (03_07)
- Visualize Raster Data with leaflet (03_08)
-
Wrapping Up
- You Did It!
Mapping with R
Basics of Using the raster Package (01_15)
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This lesson is called Basics of Using the raster Package (01_15), part of the Mapping with R course. This lesson is called Basics of Using the raster Package (01_15), part of the Mapping with R course.
Transcript
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Learn More
At the beginning of this video I advised loading the tidyverse
package after raster
to reduce your chance of getting a headache. This is because both packages contain a function called select()
and it’s very common to use that function when using tidyverse workflows. When loading the tidyverse the package emits a message informing you of functions with conflicting names, which include the syntax to explicitly call a function:
package_name::function_name()
Using this code will make your function choice explicit and is a more strict way to ensure the code you’re expecting to run is run. If you have any interest in developing R packages in the future then you’ll learn more about this kind of thing.
The land cover data file we use in this video is categorised into 14 land use types that come from the UMD Land Cover Classification. It’s very much an out-of-date land cover classification scheme so has little application outside of this example exercise. There’s not a universally accepted land cover classification scheme in existence, and this dataset is widely used in blogposts and so I think it’s useful to demonstrate how to work with RasterLayer objects.
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