Overview
Poor mapping results are one of the most common causes of support tickets across all drone platforms. In most cases, the issue is not faulty hardware, but problems with mission planning, settings, environmental conditions, or workflow.
This article explains the most common causes of bad data, how to recognise them, and what to change to get reliable, high-quality outputs.
What “Poor Mapping Results” Usually Means
Customers typically report problems such as:
Blurry or soft imagery
Holes or gaps in the model
Warped or melted-looking terrain
Inaccurate measurements
Point clouds that look noisy
Misaligned orthomosaics
Inconsistent results between flights
Data that “looks fine in the air” but fails in processing
Almost always, these issues come from how the data was captured, not from the drone itself.
1. Flying Too Fast
Flying too fast reduces image sharpness and overlap quality.
Common symptoms:
Motion blur in photos
Poor feature matching in processing
Patchy or distorted models
Best practice:
Slow down for higher accuracy work
Prioritise image quality over speed
Especially critical in low light
This affects all mapping platforms.
2. Insufficient Image Overlap
Low overlap is one of the biggest causes of broken models.
Common symptoms:
Holes in the reconstruction
Sections that fail to process
Misaligned tiles
Best practice (general guidance):
Front overlap: at least 75–80%
Side overlap: at least 65–75%
Increase overlap for:
Forested areas
Urban environments
Reflective surfaces
Complex structures
3. Flying Too High (Low Ground Resolution)
Higher altitude = less detail.
Common symptoms:
Soft-looking models
Poor edge definition
Difficulty resolving small features
Best practice:
Match altitude to required Ground Sample Distance (GSD)
For high-accuracy work, fly lower with higher overlap
Do not assume RTK can compensate for poor resolution
RTK improves positioning, not detail.
4. Poor Lighting Conditions
Lighting has a major impact on photogrammetry.
Problematic conditions:
Very low sun angles
Strong shadows
Overcast with flat light
Highly reflective surfaces
Changing light during long missions
Common symptoms:
Inconsistent textures
Warped surfaces
Difficulty matching features
Best practice:
Fly in consistent lighting where possible
Avoid very early morning / late evening for photogrammetry
Avoid reflective surfaces like water or glass
5. RTK Not Actually Working
Many users believe RTK is active when it is not.
Common symptoms:
Inconsistent alignment between flights
Measurements that are metres out
Poor geolocation accuracy
Best practice:
Always check RTK status:
FIX = good
FLOAT = reduced accuracy
NONE = no RTK benefit
Do not assume RTK is working just because it is enabled
6. Incorrect Use of GCPs (Ground Control Points)
GCPs can improve accuracy — but only when used correctly.
Common mistakes:
Too few GCPs
Poor distribution
Inaccurate GCP coordinates
GCPs placed in shadows
Using unmeasured “visual markers”
Symptoms:
Distorted models
Localised warping
Conflicting accuracy results
If GCPs are used, they must be placed and measured properly.
7. Terrain Follow Errors
Terrain follow is useful but not foolproof.
Common symptoms:
Inconsistent altitude across the site
Variable GSD
Uneven model quality
Causes:
Poor underlying elevation data
Very steep terrain
Sudden elevation changes
Best practice:
Use terrain follow carefully
Validate mission preview before flying
Increase overlap when terrain varies significantly
8. Wind Impact
Wind affects stability and image consistency.
Common symptoms:
Tilted images
Motion blur
Inconsistent overlap
Distorted vegetation models
Best practice:
Avoid mapping in strong or gusty winds
Increase overlap in windy conditions
Expect poorer results in vegetation-heavy areas
9. Wrong Camera Settings
Incorrect camera configuration can ruin data.
Common issues:
Auto ISO too high (noise)
Shutter speed too slow (blur)
Incorrect focus
Shooting JPEG when RAW is required
Incorrect aspect ratio or resolution
Best practice:
Use mapping presets where available
Ensure sharp focus
Use appropriate shutter speed for lighting and speed
Do test flights on critical jobs
10. Processing Settings Don’t Match Capture Settings
Good data can still produce bad results if processed incorrectly.
Common issues:
Wrong coordinate system
Wrong camera model selected
Over-aggressive filtering
Incorrect quality settings
Misconfigured RTK/GCP settings
Symptoms:
Misalignment
Scale errors
Unexpected distortion
Always check:
Coordinate system
Units
Accuracy reports
Processing quality settings
What RTK Does NOT Fix
RTK improves position accuracy, but it does not fix:
Motion blur
Low overlap
Bad lighting
Poor flight planning
Wind issues
Wrong camera settings
Bad processing choices
RTK is one part of the workflow, not a replacement for good practice.
A Simple Way to Think About Mapping Quality
Good results require all three:
Good flight planning
Good data capture
Good processing settings
If one of these fails, the final output will suffer.
Top 10 FAQs
Why does my map look blurry even though I used a good drone?
Usually caused by flying too fast, poor lighting, or incorrect camera settings.Why are there holes in my 3D model?
Most commonly due to insufficient overlap or difficult surfaces like water, glass, or dense vegetation.Does RTK guarantee perfect accuracy?
No. RTK improves positioning but does not fix poor data capture or processing issues.Why does my data look fine in flight but fail in processing?
Real-time previews do not reveal all quality issues. Problems often appear only during reconstruction.How much overlap should I use?
At least 75–80% front and 65–75% side for most projects. Increase overlap for complex areas.Why are my measurements inconsistent between flights?
Often caused by RTK not achieving FIX, poor GCP use, or inconsistent mission planning.Can strong wind really affect mapping quality?
Yes. Wind introduces motion, blur, and overlap issues that processing software struggles with.Do I always need GCPs if I use RTK?
Not always, but GCPs may still be required for validation or certain professional standards.Why does terrain follow sometimes make results worse?
Poor elevation data or extreme terrain changes can cause inconsistent altitude and resolution.Is bad mapping usually a drone fault?
No. In most cases, poor mapping results are caused by workflow and setup issues, not hardware.