R sf Spatial Data Cheat Sheet for CRS, Joins and Geometry
A practical sf reference for geometry columns, coordinate systems, spatial joins, clipping, validation and export.
What this reference covers
sf keeps attributes, a geometry column and coordinate reference information together. Filtering, joining, clipping and exporting therefore require checks on both ordinary fields and the validity of spatial relationships.
Coordinate systems are the most common source of subtle errors. Longitude and latitude are useful for location display but are not automatically planar distance or area units. Overlay operations also need attention to axis order, units, geometry type and precision.
A validation-first workflow
Inspect a small sample, identify the geometry type and CRS, transform to a suitable reference before measuring, and check feature counts after each spatial operation. Before export, validate geometry, encoding, fields and target-format constraints.
Maintenance note
The sheet is a function reference, not a substitute for CRS selection, measurement-error assessment or topology work. Spatial files can contain precise locations and sensitive attributes; sanitize them before sharing. Content review date: 2026-08-23.
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R sf spatial-data study guide
Inspect geometry and CRS first, choose a suitable spatial reference, perform one operation on a small sample and validate the result before export.
Before you start
- Know basic R data-frame filtering and joins.
- Prepare sanitized point, line or polygon data with a known CRS.
- Record the source, units and intended output system for the sample.
Quick start
- 01
Inspect geometry and CRS
Check the geometry column, feature type, coordinate reference system, empty geometries, coordinate range and units.
- 02
Align the spatial reference
Transform datasets to a suitable CRS before overlay or measurement, distinguishing geographic display coordinates from planar units.
- 03
Run one spatial operation
Choose intersection, containment, clipping, buffering or a spatial join and inspect feature counts and fields on a small sample.
- 04
Validate and export
Check geometry validity, duplicate features, coordinate range, attributes and encoding, then export while preserving CRS metadata.
Usage tips
- Do not treat longitude and latitude differences as planar distance or area without a measurement-appropriate CRS.
- Spatial joins may create one-to-many rows; inspect row-count and relationship changes before export.
- For large datasets, clip the region, simplify geometry or use a spatial index before scaling the operation.
Troubleshooting and uninstall
Why are layers offset after overlay?
Compare the CRS, axis order and coordinate range of both objects, transform them consistently and redraw instead of manually swapping coordinates.
Why did a spatial join create more rows?
Check for one-to-many matches, overlapping polygons or duplicate geometry, then decide whether to preserve all relations or aggregate them.
Frequently asked questions
How is an sf object different from an ordinary data frame?
It keeps a geometry column and spatial reference metadata alongside regular fields, so spatial operations affect both geometry and attributes.
When should a CRS be transformed?
Check and align CRS before overlaying different sources or measuring distance and area; geographic coordinates are not automatically measurement units.
What should be checked before exporting spatial data?
Check geometry validity, CRS, field types, encoding and target-format limits, then reopen a sample to verify location and attributes.