Make sure you can install and load all packages. This includes terra and sf, but also the tidyverse.

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Next, go to https://www.naturalearthdata.com and download the “Small scale data, 1:110m” > “Cultural” > “Admin 1 – States, Provinces” data set. Additionally, download the “NLCD 2019 Land Cover (CONUS)” data set from https://www.mrlc.gov.

Once you downloaded all the data, read it into your R Session using the corresponding packages.

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Make sure both the vector and the raster data have the same CRS (Hint: It’s often faster to project vectors instead of raster. If projecting the raster, have a look at the ‘method’ argument).

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Next, remove Alaska and Hawaii from the states vector because there is no NLCD data for these states. Next select only the 5 largest states in area

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First plot the NLCD data and add the largest states to the map. Try to use the region as shape fill.

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Now, pick one state (your home state, a state you recently visited, a state you want to visit, …) and get the NLCD data for that state only.

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Next, get all values of the cropped NLCD data and remove all NA and NaN values. Calculate the relative amount of all remaining values. Which one is the most dominant land-cover class in your state?

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Last, try to reclassify the raster into less classes (e.g., use the bigger classification found atNLCD classes)

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