FAQ
LiDAR processing, answered.
Straight answers on strip adjustment, full-waveform extraction and the accuracy you can actually prove. Don't see your question? Talk to us →
Strip adjustment: StripAlign
Which errors does StripAlign actually correct?
From swath overlaps alone, it estimates and removes boresight, lever-arm and high-frequency trajectory drift, registering overlapping flight lines onto each other. You get lower inter-swath discrepancy and better relative and absolute accuracy, fully automatic, even on very large datasets.
Do I still need calibration flights or ground control?
No dedicated calibration lines: alignment and calibration are computed from the overlaps in your regular flight lines. A standard calibration cross works, but any set of overlapping lines will do — they need not be parallel or perpendicular. Ground control stays optional: a GCP file can be supplied to constrain horizontal accuracy and for fast QC, while boresight, lever-arm, internal geometry and high-frequency drift corrections are computed from the data itself. Flying low, cutting flight-line edges and adding calibration lines are exactly the money-wasting practices this is meant to remove.
Which platforms, sensors and formats are supported?
Airborne LiDAR first, plus most UAV scanners and some sonar point clouds. Input is LAS/LAZ 1.5 or ASCII separate flight lines with an SBET/SOL/TRJ/POF/BIN/ASCII position & orientation file; PulseWaves geometry is corrected too when the PLS/PLZ files come with the LAS data. It is sensor-agnostic, handles multi-channel scanners such as the Riegl 1560 family and dual VUX, and already runs in production inside Inertial Labs RESEPI and GeoCue True View EVO. Large, complex projects use groups and reference strips, and corridor mapping with limited overlap is supported.
Full-waveform: WavEx
What does full-waveform recover that discrete returns miss?
WavEx extracts 3D points directly from the raw full waveform, recovering returns that on-board discrete pipelines discard. The result is denser, cleaner point clouds with more detail, especially at high altitude and in difficult cases with low vegetation.
Does it help under vegetation and at high flying altitude?
Yes. Recovering low-amplitude returns is exactly where full-waveform pays off: more ground points under vegetation and usable density even at high altitude, where discrete systems thin out.
Is waveform processing fast enough for production volumes?
Yes. Decoding, processing and georeferencing run in a single pass, so it stays fast on production volumes instead of adding a slow offline waveform step.
Accuracy, QA/QC & delivery
What is in an uncertainty map, and how do I use it for QC?
Uncertainty is computed, not assumed. WavEx exports per-point range and intensity uncertainty as optional extra attributes, estimated from the decomposed peak parameters. StripAlign returns QC maps, 3D error analysis, Z-differences, point density, hill shade and roughness maps, with reports meant to be read quickly. Use them for QA/QC and acceptance: see where the data is reliable and where it is not, and focus your checks there. Mapping the spatial accuracy of a product, with uncertainty propagated rigorously, is the feature the company was built on.
Is a single RMSE enough to describe accuracy?
No. A global RMS error is an inadequate description of uncertainty, because data density and quality vary across a project. Accuracy is reported spatially instead: a predictive error for each location, obtained by rigorous error propagation. On the AutoProbaDTM project, a 200 km² DEM at 1 m GSD was delivered tile by tile with maps of predictive accuracy, point density, peak widening, inter-strip discrepancy and intensity.
What OS does it run on, and can I evaluate it first?
StripAlign and WavEx both run on Windows, Linux and macOS, 64-bit. Full email support is included in the subscription, with remote calibration, testing and consulting available on top. To try them, request a demo license: you get a 30-day floating license with fully functional products. You can also send us a sample dataset for a free evaluation.
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