EUDR & Traceability

Coffee Plot Geolocation

Geolocation is the data requirement that most changes what has to happen at origin, because unlike documentation it cannot be produced from existing records. This page covers what is collected, how, and what the practical limits are.

Last reviewed August 20263 min read

Quick answer

Plot geolocation records where coffee was produced, as either a point coordinate or a boundary polygon. Collection is a field exercise: someone visits each plot with a GPS-enabled device. Across a smallholder base of hundreds or thousands of farms, that is a substantial programme that must be planned before the harvest.

Scope of this section

This page describes what an origin supplier can provide to support an operator’s due diligence. It is not legal advice and it is not a statement of your obligations. The regulation, its guidance and its application timeline have been amended; confirm the current requirements from the official text and your own advisers.

Points and polygons

Two forms of plot geolocation
	Point coordinate	Boundary polygon
What it is	A single latitude/longitude for the plot	A closed series of coordinates describing the boundary
Collection effort	Minutes per plot	Walking the perimeter — much longer
Typical use	Smaller plots	Larger plots
Analytical use	Cross-reference against forest cover at a point	Area-based analysis
Practical availability	Achievable across large smallholder bases	Realistic for larger farms and estates
Error sensitivity	Point placement matters on fragmented plots	Perimeter accuracy and closure matter

For East African smallholder coffee, points dominate simply because plots are small and numerous. Anyone promising universal polygon coverage across thousands of sub-hectare farms should be asked to demonstrate the field programme that produced it.

How collection actually works

A geolocation collection programme

Step 1
Define the supply base
Establish which producer groups and stations feed the programme, and obtain their farmer lists.
Step 2
Equip and train enumerators
GPS-capable devices, a data collection application, and training on plot identification and consent.
Step 3
Field visit
Visit each plot, record the coordinate or walk the boundary, and capture the farmer and plot identifiers that link the record to deliveries.
Step 4
Validate
Check for duplicates, impossible coordinates, plots outside the expected area, and unclosed polygons.
Step 5
Link to deliveries
Connect farmer identifiers to the station’s cherry delivery records so the data ties to actual lots.
Step 6
Maintain
Update between seasons as farmers join, leave or change the station they deliver to.

The maintenance problem

A geolocation dataset is not collected once. Farmers change which station they deliver to, plots are subdivided on inheritance, and new producers join. A dataset that is not maintained becomes progressively less connected to the coffee actually being shipped.

Accuracy and its limits

Consumer GPS accuracy under tree canopy and in steep terrain is materially worse than in open ground — and coffee grows under shade on hillsides.
Plot fragmentation. A farmer with three separate small plots has three locations, not one. Recording one and treating it as the farm is a data quality problem.
Point placement. A point recorded at the farm gate rather than in the coffee is a different location; enumerator training matters.
Duplicate records. Two enumerators recording the same plot under different farmer identifiers inflates apparent coverage.
Coverage claims. "95% of our supply base geolocated" is only meaningful if the denominator is defined and the linkage to actual deliveries is demonstrated.

Data protection

Farmer names, identifiers and plot locations are personal data. Collecting and transferring them creates obligations — for informed consent, for secure handling, and for limiting onward disclosure to what is necessary.

Consent should be obtained and recorded at collection, in a language the farmer understands.
Data shared with buyers should be limited to what the due diligence process actually requires.
Aggregated or pseudonymised forms are often sufficient for analysis and reduce exposure.
Retention periods and deletion should be defined rather than left open.

Plan geolocation before the harvest

If a programme needs plot data, the collection has to be arranged ahead of the crop. Tell us the origins and the timeline and we will scope what is feasible.

Discuss a programme

Frequently asked questions

What is plot geolocation for coffee?

A record of where the coffee was produced, as either a point coordinate or a boundary polygon for the plot. It is collected in the field with GPS-enabled devices and linked to the farmer and delivery records that connect it to actual lots.

Do you need polygons or are points enough?

It depends on the plot and on what the operator’s process requires. For small smallholder plots, point coordinates are the realistic and widely used form; polygons are more practical on larger farms and estates. Establish which your process needs before the collection programme is designed.

How accurate is smallholder geolocation data?

Accuracy is limited by consumer GPS performance under tree canopy and on steep terrain, by plot fragmentation, and by enumerator training. It is good enough for the purpose when collected carefully; it is not survey-grade, and claims that imply otherwise should be examined.

Is farmer geolocation data personal data?

Yes. Farmer identifiers and plot locations are personal data and attract data protection obligations — informed consent, secure handling, limited onward disclosure and defined retention. This should be addressed in the programme design, not afterwards.

Tell us the coffee you need

Lots can be specified by origin, region, process, grade, screen, moisture, defect tolerance, crop year and packaging. Send what you know and we will confirm what each origin realistically supports.

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