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As recommended raster::extract will accomplish what you are after. However, from a computational speed and modernization standpoint, I would recommend using the terra package, which is a replacement f …

The Modifiable Aerial Unit Problem (MAUP) is a change of support issue associated with arbitrary aggregate units. Two classic examples are census tracks and wildlife game units. These have been found …

Here is an R solution that uses the mode of the observed distribution. Create some example data require(raster) r <- raster(ncol=36, nrow=18) r[] <- sample(1:3, ncell(r), replace=TRUE) …

I have moved to using the exact_extract function in the exactextractr package. One nice thing is that it returns all cell intersections with the fractional proportion of each cells intersection. You c …

You can write a simple function using prop.table and table to return proportions of multiple classes. The catch is that you have to know what all of the classes are before hand so you can fix the numb …

Here are two ways to do this. The raster extract function is the common approach. However, the zonal.stats function uses velox under the hood, which speeds things up considerably. You will not see muc …

You could approach this as a raster/vector integration problem, where your course resolution data are essentially sampling blocks represented as polygons. First, let's create your example data. li …

In R, you can extract the raster data for each polygon and then summarize it. First, lets create some data (FYI, you can read in a shapefile using raster::shapefile or rgdal::readOGR and a raster usin …

I am not sure if you want the ratio based on the "real value" of the polygon(s) areas or the areas of the cells intersecting them. Here is some example code that uses all cells intersecting the polygo …