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Data processing and quality evaluation of a boat-based mobile laser scanning system.

Matti Vaaja¹, Antero Kukko, Harri Kaartinen

¹Department of Real Estate, Planning and Geoinformatics, Aalto University, Aalto FI-00076, Finland. Matti.T.Vaaja@aalto.fi.

Sensors (Basel, Switzerland)

|September 20, 2013

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Boat-based mobile mapping systems (BoMMS) efficiently collect river data. Improved processing enhances shoreline mapping and shallow bathymetry, offering accurate terrain and vegetation point classification for environmental studies.

Area of Science:

Geomatics Engineering
Environmental Science
Hydrography

Background:

Mobile mapping systems (MMSs) offer efficient data collection for challenging topographic and urban features.
Boat-based mobile mapping systems (BoMMS) are emerging tools for riverine environment mapping.
Existing BoMMS research has focused on elevation accuracy and detecting fluvial geomorphological changes.

Purpose of the Study:

To investigate data processing steps and quality for BoMMS data in river environments.
To generate accurate terrain, vegetation, and bathymetry points.
To evaluate the accuracy of ground point classification and assess data density and accuracies.

Main Methods:

Developed and applied an improved data processing workflow for BoMMS data.

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Implemented noise filtering, shoreline detection, and underwater point identification.

Classified ground points and compared them with manually classified data.

Assessed spatial variations in ground point density and evaluated elevation and vertical accuracies.

Main Results:

The improved processing successfully identified multipath reflections and delineated shorelines.
Demonstrated the capability to measure bathymetry in shallow (0-1 m), clear water.
Achieved accurate classification of ground points, with evaluated spatial variations in density.
Assessed elevation and vertical accuracies of the BoMMS data.

Conclusions:

The enhanced data processing significantly improves the utility of BoMMS for riverine environments.
BoMMS data, with this processing, can reliably generate terrain, vegetation, and shallow bathymetry data.
This methodology provides a valuable tool for environmental monitoring and mapping in river systems.