How Precision Farming Works: RTK Accuracy & Real Workflow

Estimated reading time: 7 minutes

In the same field, soils, moisture, and crop potential can change every few meters, so treating every acre the same usually wastes inputs and leaves yield on the table. Precision farming fixes that by combining field data with accurate positioning so your machine does the right thing in the right place, every pass. This guide explains the real-world workflow (GNSS/RTK, VRT, sensors, mapping).

Summary

Precision farming integrates high-resolution field data and GNSS positioning to optimize machine actions in real-time. With benefits spanning reduced overlaps, input savings, accurate recordkeeping, and improved consistency across seasons, it is a cornerstone of sustainable and efficient agriculture. The workflow includes measurement, georeferencing with GNSS/RTK, spatial analysis, prescription generation, execution with section control and autosteer, then verification through as-applied mapping and yield analysis.

Key takeaways

• Precision farming is a whole workflow: measure, georeference, analyze, prescribe, act, and verify.
• RTK delivers high repeatability: critical for strip-till, planting, and controlled traffic farming.
• Section control and autosteer reduce fatigue, overlap, and missed spots.
• Start simple with soil sampling, boundaries, and clean guidance lines and layer in VRA with ROI clarity.

What is Precision Farming? Definition And Problems

Precision farming (often called precision agriculture) is managing crops, inputs, and operations based on measured differences within a field by using maps, sensors, and accurate GNSS positioning to vary actions by location. That variability is real: a sand ridge dries fast, a low spot stays wet, organic matter and drainage shift by the swath. Uniform rates over those differences create waste and risk.

Example: if a low spot consistently yields less due to waterlogging, applying the same seed and nitrogen rate as the best zone overspends inputs without improving yield. Targeting rates to zone potential supports input optimization, reduces nutrient runoff, and stabilizes performance year to year.

Quick contrasts: precision farming focuses on field-level variability and execution (guidance, VRT, section control). Digital farming is broader—records, traceability, dashboards. Smart farming leans into automation/IoT/robotics. One common mistake: assuming any GPS equals precision farming; accuracy and repeatability levels matter for results.

Real pains it solves include overlaps and gaps, operator fatigue, inconsistent passes across seasons, runoff risk, and poor documentation. Guidance lines reduce missed or double-applied strips. Section control prevents re-spraying on point rows. As-applied maps prove what happened and feed learning. These are core precision farming benefits and challenges to weigh when you plan investments.

Within-field variability and zones

"Management zones" are areas grouped by similar yield potential or soil behavior, built from yield history, soil sampling, soil electrical conductivity (EC) scans, and imagery. Zones are simpler to start; grids offer detail but demand stronger data discipline. With that foundation, the precision farming technology stack explained in the next section shows how data becomes decisions.

Precision Farming in Agriculture Workflows

1. Measure: Collect yield monitoring, soil sampling results, EC, soil moisture sensors, machine logs, and NDVI/multispectral imagery from satellite or drone.
2. Georeference: Tie every datapoint to reliable GNSS positions; higher-precision work uses RTK so maps align pass-to-pass and season-to-season.
3. Analyze: In GIS, compare layers, clean outliers, and build management zones or grids. Add notes about weather and operations.
4. Decide: Create prescriptions—variable rate application (VRA) for seed, nutrients, or lime based on zones and business goals.
5. Act: Send prescriptions to controllers, run autosteer on guidance lines, use section control, and (where supported) PWM for precise flow.
6. Verify: Review as-applied maps and yield monitoring to confirm execution and refine next season.

High-value layers to prioritize: clean field boundaries, guidance lines, three or more years of yield maps, soil test results, and as-applied records. Watch for data noise: single-date imagery without ground truth, uncalibrated sensors, and inconsistent field naming. If you can't explain how a layer changes a decision, don't collect it yet.

Planned vs executed always differ—latency, calibration, speed changes, section timing, and offset errors creep in. If a sprayer section turns off 0.5 seconds late at 12 mph, the overlap can be several feet, which shows up in chemical cost and crop stress. As-applied + yield monitoring improves traceability and supports sustainability reporting to customers.

Data stewardship basics

Farm data ownership means who can access, reuse, or sell your machine and field data under the agreement. Ask three buyer questions: What export formats are supported (shapefile, ISOXML, CSV)? What permission controls exist for staff and partners? How can I delete data? Interoperability across displays, software, and a decision support system is where headaches or savings emerge.

Precision Farming Technologies You Actually Use

Guidance and autosteer: Autosteer uses GNSS to keep the machine on a guidance line with minimal drift, reducing overlaps and gaps and lowering operator fatigue. Pass-to-pass repeatability matters for consistent swaths. A 36 m sprayer in irregular fields can waste product on point rows; autosteer plus section control cuts re-spraying and missed corners. For precision farming for small farms, basic mapping and tractor guidance systems often deliver the first big wins before VRT.

VRA vs section control vs PWM: Variable rate application changes the rate by location from a prescription map (e.g., more N in high-response zones). Section control turns boom/row sections on and off to avoid overlap—rate stays the same when on. PWM (pulse-width modulation) rapidly pulses valves so sprayers vary rate while maintaining steadier pressure and droplet size. Calibrate flow meters, speed sources, and boom offsets, or your as-applied maps won't match reality.

Sensors and imagery: NDVI highlights relative greenness/biomass; it shows patterns, not causes. Cloud cover, canopy closure, and residue can mislead. Ground-truth with scouting and soil tests. Example: imagery shows a weak zone; you find compaction—so you change tillage/traffic patterns instead of just adding fertilizer.

Interoperability buying checklist

• ISOBUS support: ISO 11783 compatibility reduces brand lock-in.
• Prescription file compatibility: Shapefile, ISOXML, or vendor formats accepted.
• As-applied export: Get clean, timestamped maps out for audits and analysis.
• Raw yield access: Don't settle for only summaries; you need raw yield monitoring data.
• Guidance portability: Can AB lines move between displays?

RTK GPS Accuracy For Precision Farming

Accuracy vs repeatability: Accuracy is how close your reported position is to the true Earth location. Repeatability is how reliably you return to the same path today and next season. For planting, strip-till, controlled traffic farming, and inter-row work, repeatability is the real prize.

Correction tiers: Uncorrected GNSS is fine for rough location, not tight guidance. SBAS/DGPS boosts general accuracy. RTK uses a correction signal from a base station or network for centimeter-level repeatability. PPP delivers decimeter accuracy after convergence but lacks RTK's repeatability.

Delivery and pitfalls: NTRIP sends RTK corrections via cellular internet to your receiver. Or use radio links. Pitfalls include signal blockages, poor antenna mounting, or mismanaged guidance lines.

Professional RTK services like RTKdata.com provide over 20,000 stations in 140+ countries—enabling NTRIP delivery of corrections without your own base station.

• Mount/measure: Keep the antenna rigid and centered; measure offsets carefully.
• Line discipline: Save and reuse the same guidance lines for repeatability.
• Latency watch: Monitor correction age; if it spikes, slow down or pause critical work.

Tasks and needed precision

• Broadcast spreading: lower precision often acceptable.
• Spraying with section control: moderate precision helps reduce overlap.
• Planting/strip-till: RTK is commonly used for repeatable rows and controlled traffic farming.
• Orchards/vineyards: repeatable guidance lines improve lane management and reduces crop damage risk.