DRONEWERX Accelerates RTK Drone Mapping in Southern Nevada with RTKdata

Estimated reading time: 7 minutes

"It has worked great."
Tim Davis, DRONEWERX

Executive summary

A DRONEWERX crew needed to capture a repeatable, high-accuracy map of a large facility footprint in Southern Nevada (multiple structures and yard areas visible on the mission basemap). By using RTKdata network corrections (NTRIP) with an RTK-enabled DJI mapping workflow, the pilot avoided time-consuming ground control point (GCP) deployment and eliminated the logistics of bringing and configuring a local RTK base station. The result: a faster field operation, lower labor cost per mission, and less risk of rework, while maintaining centimeter-level positioning embedded in the imagery metadata, well suited for professional mapping deliverables.

Project snapshot

The challenge

Mapping large, remote facilities in the Nevada desert is a perfect use case for drones, but it comes with practical constraints that can make traditional survey-style workflows expensive:

1. Time on site is costly. Access windows, security coordination, and site safety briefings often compress the time available to capture data.
2. The footprint is big. Large, open sites increase walking distances if GCPs must be placed throughout the area.
3. Field conditions are unforgiving. Heat, dust, and exposure can turn "just a few extra steps" into a real operational burden.
4. The deliverable must be defensible. When outputs are used for engineering, construction planning, or asset documentation, teams need predictable georeferencing and repeatable results.

Common alternatives (and why they slow teams down)

Before network RTK became a standard field tool, most drone mapping crews relied on one of two methods:

A) GCP-heavy photogrammetry (no RTK on the aircraft)

GCPs can produce excellent accuracy, but they add a lot of labor: deploying targets, measuring them with a GNSS rover, and then manually tagging them in processing. On larger sites, the GCP portion alone can easily add 1–3 hours to a mission—sometimes more, depending on access restrictions and the number of control points required.

B) Bringing a local RTK base station

Running your own base can reduce GCP needs, but it introduces new overhead: transporting extra hardware, setting the base up correctly, confirming coordinates (or running a base averaging routine), managing the correction link, and tearing everything down afterward. Even when everything goes right, base setup/teardown commonly costs 30–60 minutes, plus another system that can fail or be misconfigured.

The RTKdata approach

DRONEWERX used RTKdata as the correction source for the RTK-enabled drone mapping mission. Practically, that meant the crew could arrive on site and:

• Connect to RTKdata via NTRIP in minutes
• Confirm RTK fix and satellite tracking on the controller
• Launch the automated mapping route immediately
• Capture imagery with RTK-corrected positions written into each photo

This workflow removes the "extra project" that base stations and GCPs often become. For a production mapping team, that simplicity matters as much as raw accuracy: fewer steps, fewer things to troubleshoot, and more consistent outcomes from job to job.

Field workflow (what changed in practice)

1) Pre-flight: Route planning and RTK connection

The pilot set the mapping corridor (parallel flight lines sized for full site coverage and overlap) and connected to RTKdata corrections. With RTK confirmed the crew could proceed without staging a base station.

2) Capture: Automated route execution

The aircraft flew the programmed route at ~200 ft AGL while collecting a dense photo set (~250 images planned). The "lawnmower" pattern is designed to produce consistent forward/side overlap so photogrammetry software can build a clean orthomosaic and 3D model.

3) Processing: Faster alignment and cleaner georeferencing

With RTK-corrected photo positions, the dataset typically aligns faster and requires less manual control-point work. Many teams still use check points or limited control for verification, but RTK substantially reduces the amount of ground work required for routine mapping deliverables.

Results: time, cost, and operational risk

While every site varies, the savings from network RTK are consistent in real-world operations:

Time savings

• Versus GCP-heavy workflows: commonly 2–3 hours saved per mission by eliminating target placement, GNSS point collection, and the extra processing steps tied to GCP marking.
• Versus deploying a local base station: commonly 30–60 minutes saved per mission by removing base setup/teardown and related troubleshooting.

Cost impact (typical, conservative estimate)

Commercial drone mapping time (pilot + vehicle + overhead) often lands around $100–$200/hour. Using conservative math, saving 2 hours can avoid roughly $200–$400 in direct operating cost per project—before counting the value of finishing earlier, reducing overtime, or fitting additional jobs into a week.

Risk reduction (often the biggest "hidden" win)

• Fewer failure points: No base tripod to disturb, no local radio link to debug, fewer "restart the mission" events.
• Less rework: Consistent georeferencing reduces the odds of misalignment that forces a re-flight.
• Improved safety: Less walking to set GCPs means less exposure to heat, traffic, and site hazards.

Conclusion

For industrial/infrastructure-style mapping in Southern Nevada, RTKdata helped DRONEWERX turn an RTK-capable drone into a faster, more scalable production tool. The team reduced on-site labor and complexity while maintaining high-accuracy georeferencing appropriate for professional mapping outputs. For operators who work across wide geographic areas and tight schedules, the key benefit is repeatability: connect, fly, process, deliver—without building every mission around ground control or base station logistics.