Next Article in Journal
Estimating Forest Aboveground Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China
Previous Article in Journal
Comparative Estimation of Urban Development in China’s Cities Using Socioeconomic and DMSP/OLS Night Light Data
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2014, 6(9), 7857-7877; doi:10.3390/rs6097857

MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density

National Centre for Geocomputation, National University of Ireland, Maynooth, Co. Kildare, Ireland
*
Author to whom correspondence should be addressed.
Received: 1 July 2014 / Revised: 18 August 2014 / Accepted: 18 August 2014 / Published: 25 August 2014
View Full-Text   |   Download PDF [2257 KB, uploaded 25 August 2014]   |  

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. View Full-Text
Keywords: point density; mobile mapping systems; performance; LiDAR point density; mobile mapping systems; performance; LiDAR
Figures

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Cahalane, C.; McElhinney, C.P.; Lewis, P.; McCarthy, T. MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density. Remote Sens. 2014, 6, 7857-7877.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top