Overlaying shapefile layers in R

Overlaying Shapefile Layers in R: A Human’s Guide to Spatial Harmony

Ever felt like you’re drowning in spatial data? Like you’ve got maps coming out of your ears, but they just won’t talk to each other? I’ve been there. Geospatial analysis is all about bringing different data sources together, and often, those sources are shapefiles. R, thankfully, is a total powerhouse for this, especially with packages like sf, sp, and raster. Think of them as your spatial Swiss Army knife. This guide is all about showing you how to overlay shapefile layers in R, so you can finally make sense of that data and unlock some real insights.

Shapefiles: What Are They, Really?

Shapefiles are basically the bread and butter of geospatial data. They’re like digital containers holding geometric locations – think points, lines, and polygons – along with all sorts of descriptive information. A single shapefile is actually a collection of files, like the .shp (where the actual shapes live), the .dbf (that’s the attribute table with all the juicy details), and the .prj (which tells you where on Earth this data belongs).

In R, the sf package is the modern way to go. It treats spatial data like regular data frames, which makes life so much easier. The older sp package is still kicking around, and you’ll probably run into it at some point, so it’s worth knowing the basics.

Your Essential Toolkit for Overlay Magic

• sf: This is your main squeeze for reading, writing, and generally wrangling vector data. It’s the cool kid on the block.
• sp: The old faithful. Still gets the job done, especially with older code or specific packages.
• raster: For when you need to bring raster data (like satellite imagery) into the mix. Think extracting elevation data within a polygon.
• dplyr: Data manipulation is key, and dplyr is your best friend for cleaning up and processing attribute data after overlays.
• rgdal: This one’s a bit under the hood, but it’s essential for reading and writing different geospatial formats and handling coordinate system transformations. Consider it the translator between different spatial languages.

Bringing Your Shapefiles into R

First things first, you need to get your shapefiles into R. The st_read() function from the sf package is your go-to:

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