SpatVector: represent vector-based point, line, or.In comparison to the raster package data models SpatRaster: for raster data and limits memory usage.The terra package introduces the following new classes: Here are some helpful links for learning terra: It also supports working with largerĭata sets as it is not required to read entire raster grids into terra works toĪlleviate some of these issues. Memory issues if large raster datasets are used. The raster package can be slow and can result in Originators of raster have released the terra package The raster package has been a central toolįor working with geospatial data in R for years. Which is replacing the raster package for working with We’ve seen this CRS before with our Harvard Forest study site ( point_HARV).In this module, we will focus on the terra package, However, if we have other data in the UTM Zone 18N projection, it’s muchĮasier to use the st_crs() function to extract the CRS in proj4 format from that object and assign it to our new spatial object. From here, we can extract the proj4 string for UTM Zone 18N WGS84. Projection on the Spatial Reference website, which contains a list of CRS formats for each projection.

To create the proj4 associated with UTM Zone 18 WGS84 we can look up the While the projection is not specified as a column, we are given information about a UTM Zone. For these data we know the datum is WGS84. We need to know the datum, the projection, and in some cases a zone. We learned about the components of a proj4 string. When Vector Data Don’t Line Up - Handling Spatial Projection & CRS in R

geodeticDa: WGS84 – this is geodetic datum WGS84.

The geodeticDa and utmZone columnsĬontain the information that helps us determine the CRS: But this particularįile contains CRS information this way. It is not typical to store CRS information in a column. Let’s check out the column names of our dataframe. csv will contain columns with the X and Y locations. Next, let’s explore the dataframe to determine whether it contains columns with coordinate values. Note that all of our character data was imported into R as factor (categorical) data. We now have a data frame that contains 21 locations (rows) and 16 variables (attributes). $ soilTypeOr: chr 'Inceptisols' 'Inceptisols' 'Inceptisols' 'Histosols'. $ subtype : chr 'basePlot' 'basePlot' 'basePlot' 'basePlot'. $ plotType : chr 'distributed' 'tower' 'tower' 'tower'. $ siteID : chr 'HARV' 'HARV' 'HARV' 'HARV'.

$ domainName: chr 'Northeast' 'Northeast' 'Northeast' 'Northeast'. $ county : chr 'Worcester' 'Worcester' 'Worcester' 'Worcester'. Once we import the file, we can check to see if the file contains plot coordinate as x, y attributes. To begin let’s import the HARV_PlotLoations.csv file with the locations at the NEON Harvard Forest Field Site. The sf object allows us to store both the x,y values that represent the coordinate location of each point and the associated attribute data - or columns describing each feature in the spatial object. If the text file has an associated x and y location column, then we canĬonvert it into an sf spatial object. Shapefile can be imported into any GIS software. Export the data in a shapefile format to share with our colleagues.csv file and convert to a spatial object. Text files can be opened in any program and can be converted to any type of vector file format, so it is often useful for long-term storate and sharing with others who may not be familiar with the shapefile format. While it is very common to store vector data as an Esri shapefile format and most programs can create and read that format, you may encounter data stored in a text file. This file contains x, y (point) locations for study plot where NEON collects data on The data we downloaded includes a text file called HARV_PlotLocations.csv. Spatial data are sometimes stored in a text file format (.

# Learners will have this data loaded from earlier episodes aoi_boundary_HARV <- st_read ( 'data/vector/HarClip_UTMZ18.shp' ) lines_HARV <- st_read ( 'data/vector/HARV_roads.shp' ) point_HARV <- st_read ( 'data/vector/HARVtower_UTM18N.shp' ) Spatial Data in Text Format

Convert im object into raster in r