Paper Info
Title
MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density
Abstract
Understanding how various Mobile Mapping System (MMS) laser hardware configurations and operating parameters exercise different influence on point density is important for assessing system performance, which in turn facilitates system design and MMS benchmarking. Point density also influences data processing, as objects that can be recognised using automated algorithms generally require a minimum point density. Although obtaining the necessary point density impacts on hardware costs, survey time and data storage requirements, a method for accurately and rapidly assessing MMS performance is lacking for generic MMSs. We have developed a method for quantifying point clouds collected by an MMS with respect to known objects at specified distances using 3D surface normals, 2D geometric formulae and line drawing algorithms. These algorithms were combined in a system called the Mobile Mapping Point Density Calculator (MIMIC) and were validated using point clouds captured by both a single scanner and a dual scanner MMS. Results from MIMIC were promising: when considering the number of scan profiles striking the target, the average error equated to less than 1 point per scan profile. These tests highlight that MIMIC is capable of accurately calculating point density for both single and dual scanner MMSs.
Year
DOI
Venue
2014
10.3390/rs6097857
REMOTE SENSING
Keywords
Field
DocType
point density,mobile mapping systems,performance,LiDAR
Computer vision,Data processing,Calculator,Computer data storage,Systems design,Lidar,Artificial intelligence,Scanner,Geology,Point cloud,Mobile mapping
Journal
Volume
Issue
ISSN
6
9
2072-4292
Citations 
PageRank 
References 
2
0.41
10
Authors
4
Name
Order
Citations
PageRank
Conor Cahalane1153.18
Conor P. McElhinney2313.05
Paul Lewis3363.70
Timothy J. McCarthy472.24