Transforming "Null" Geometries to Polygons in R's terra Package
Working with spatial data in R often involves managing different geometry types, and sometimes you might encounter a SpatVector with "null" geometry information. This can happen when you import data from sources that don't explicitly define the geometry type or if the data has been processed in a way that removes the geometry information.
This article will guide you through the process of assigning the "polygons" geometry type to a SpatVector with a "null" geometry type using the terra package in R.
Scenario and Initial Code
Let's imagine you have a SpatVector called my_data that contains a "null" geometry type:
library(terra)
# Create a SpatVector with null geometry
my_data <- vect(cbind(1:5, 1:5), crs = "epsg:4326")
# This creates a SpatVector with five points, but without defined geometries
print(geomtype(my_data)) # Output: "POINT"
# Let's assume you know that you need to assign a polygon geometry
The geomtype() function tells us that the my_data SpatVector currently has a "POINT" geometry type, even though it doesn't have any defined geometries.
Repurposing Existing Data for Polygon Creation
In the absence of explicit polygon data, we need to leverage the information we have to create polygons. The terra package provides versatile functions for this purpose.
One approach is to use the st_as_sfc() function from the sf package to create polygons based on existing data. However, it's essential to have a clear understanding of how the data should be converted into polygons. If you have a column containing coordinates for the polygon vertices, you can use it to create polygons. If not, you might need to use other columns as input for creating polygons.
For example, let's say you have a column named "polygon_definition" in your SpatVector that contains information about the vertices of each polygon:
# Assuming "polygon_definition" contains information about polygon vertices
# You'll need to adapt this based on your specific data structure
my_data$polygon_definition <- paste0("POLYGON((", my_data$x, " ", my_data$y, " , ", my_data$x + 1, " ", my_data$y, " , ", my_data$x + 1, " ", my_data$y + 1, " , ", my_data$x, " ", my_data$y + 1, " , ", my_data$x, " ", my_data$y, "))")
my_data <- st_as_sfc(my_data$polygon_definition, crs = "epsg:4326")
# This creates a SpatVector with polygon geometries based on the "polygon_definition" column
print(geomtype(my_data)) # Output: "POLYGON"
Now your my_data SpatVector will have "POLYGON" geometry.
Important Considerations
- Data Structure: Before you attempt to create polygons, ensure that you have the necessary information in your SpatVector to define them. This might involve coordinates, spatial IDs, or other relevant data that allows you to define the polygon boundaries.
- Spatial Integrity: Double-check that the polygons you create are spatially valid. Use the
st_is_valid()function from thesfpackage to verify this. - Data Transformation: If you need to transform the data from one coordinate reference system (CRS) to another, you can use the
project()function in theterrapackage.
Additional Resources
- terra Package Documentation: Explore the documentation to learn more about the
terrapackage functions for working with SpatVectors. - sf Package Documentation: Learn more about the
sfpackage functions for working with spatial data in R. - Spatial Data Processing in R: This resource offers a comprehensive overview of spatial data processing techniques in R.
By understanding the basics of geometry type management and leveraging the powerful functions available in the terra package, you can effectively transform "null" geometries into polygons and unlock the full potential of your spatial data.
