![]() ![]() The value of each pixel is indicative of the land use in that pixel (i.e. 1 = CORN, etc). So I did all that, and can load my raster with the easiest function ever: cache <- raster("./data/CDL_2016_49005.tif") You’ll have to unzip the files and move both files to a local data folder. Select 2016, Submit and the data should download to your computer. Next, click the little folder icon with a green arrow on it. To do this, click on the little USA map at the top of the page, select County, find Cache, then click Submit. I went to the CropScape website and downloaded data for Cache Valley in 2016. Department of Agriculture, there are more detailed categorizations for agricultural lands than for ecosystems. Since the dataset was built by the folks at the U.S. This is a categorical raster that covers most of the country from 2000 to present at a 30 meter - YES T-H-I-R-T-Y meter - resolution. For now, let’s work with a single layer of my current favorite raster dataset, the CropScape dataset. We’ll get to bricks later in the tutorial. And finally, if you’re one of the unlucky ones whose data comes in HDF4 or HDF5 data (ahem NASA, get your stuff together!), read this. ![]() And if you still feel confused about the different ways of storing raster data in the raster package, check this out. You can find the full list in the raster package documentation. I’ve encountered all of these at some point… and the raster package can handle just about all of them. There are tons of raster extensions out there. Instead, we’ll focus on learning how to load and manipulate the most commonly used types of raster data. You’ve already learned how to make a raster from scratch, so we won’t cover that here. RasterStacks can be made with multiple files (band from one file merged with a band from another file) - though these objects have to have the same extent and resolution. The main difference is that a RasterBrick can be linked to only one (though multi-layer) file. RasterBricks, and RasterStacks are great for multiband data (i.e. multiple spectral bands, observations through time).This object contains the number of columns and rows in the raster, the spatial extent, pixel values, and the projection information (stored in CRS format) A RasterLayer contains a single-layer raster.The raster package includes several raster classes: Then go download Google Earth and start playing. in near real time, all the time, anywhere. Let me pause here and state that you are some of the luckiest people to ever live because you have insanely easy access to incredible, beautiful visualizations of our precious planet. How many cars are in that parking lot by your house? How many lawn chairs in your backyard (freaking out yet?)? You get the idea.How many people live in this pixel (yes, people have done this using night light data)?.How deep is the groundwater under this pixel (see GRACE satellite)?. ![]()
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