Next Article in Journal
Inspection of Pole-Like Structures Using a Visual-Inertial Aided VTOL Platform with Shared Autonomy
Previous Article in Journal
Microwave-Based Oxidation State and Soot Loading Determination on Gasoline Particulate Filters with Three-Way Catalyst Coating for Homogenously Operated Gasoline Engines
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(9), 21989-22002; doi:10.3390/s150921989

Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

1,2,†
,
1,†,* , 1,2
,
1
,
1,3
,
1
and
4
1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430072, China
2
Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430072, China
3
School of Physics and Technology, Wuhan University, 129 Luoyu Road, Wuhan 430072, China
4
State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, 30 Xiao Hongshan Road, Wuhan 430072, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 25 July 2015 / Revised: 27 August 2015 / Accepted: 28 August 2015 / Published: 2 September 2015
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [1094 KB, uploaded 2 September 2015]   |  

Abstract

The abilities of multispectral LiDAR (MSL) as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image. View Full-Text
Keywords: LiDAR; multispectral; object classification; support vector machine LiDAR; multispectral; object classification; support vector machine
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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

Gong, W.; Sun, J.; Shi, S.; Yang, J.; Du, L.; Zhu, B.; Song, S. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification. Sensors 2015, 15, 21989-22002.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top