#Vectors and rasters series

#Vectors and rasters series

This series for information on working with multi-band rasters: Regardless of whether it has one or more bands. Byĭefault the raster() function only imports the first band in a raster However, raster data can also be multi-band, meaning that one raster fileĬontains data for more than one variable or time period for each cell. Raster statistics are often calculated and embedded in a GeoTIFF for us. In thisĬase, given we are working with elevation data, these values represent the It is useful to know the minimum or maximum values of a raster dataset. Image source: Chrismurf at English Wikipedia, via Wikimedia Commons (CC-BY). Note that the zone is unique to the UTM projection. ellps=WGS84: the ellipsoid (how the earth’s roundness is calculated) for.units=m: the units for the coordinates are in meters.The coordinate system used in the projection) datum=WGS84: the datum is WGS84 (the datum refers to the 0,0 reference for.proj=utm: the projection is UTM, UTM has several zones.Our projection string for DSM_HARV specifies the UTM projection as follows: AfterĮach + we see the CRS element being defined. The string contains all of the individual CRSĮlements that R or another GIS might need. The CRS for our data is given to us by R in proj4 format. +units=m tells us that our data is in meters. +proj=utm +zone=18 +datum=WGS84 +units=m +no_defs +ellps=WGS84

Make sure that you have these packages loaded. We will use two additional packages in this episode to work with raster data - the In the Introduction to R for Geospatial Data lesson. We will continue to work with the dplyr and ggplot2 packages that were introduced

We will also explore missing and badĭata values as stored in a raster and how R handles these elements. Rasters in R, including CRS and resolution. We willĭiscuss some of the core metadata elements that we need to understand to work with Metadata/raster attributes that are needed to work with raster data in R. In this episode, we will introduce the fundamental principles, packages and See the lesson homepage for detailed information about the software,ĭata, and other prerequisites you will need to work through the examples in this episode. Things You’ll Need To Complete This Episode Plot a raster file in R using the ggplot2 package.ĭescribe the difference between single- and multi-band rasters. Import rasters into R using the raster package. Describe the fundamental attributes of a raster dataset.Įxplore raster attributes and metadata using R.