Next Article in Journal
Investigation of Depth and Injection Pressure Effects on Breakdown Pressure and Fracture Permeability of Shale Reservoirs: An Experimental Study
Next Article in Special Issue
Simulating the Effects of the Airborne Lidar Scanning Angle, Flying Altitude, and Pulse Density for Forest Foliage Profile Retrieval
Previous Article in Journal
Barriers and Chemistry in a Bottle: Mechanisms in Today’s Oxygen Barriers for Tomorrow’s Materials
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(7), 663; doi:10.3390/app7070663

Analysis of Land Cover Classification Using Multi-Wavelength LiDAR System

Department of Civil Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Francesco Pirotti, Xinlian Liang and Qi Chen
Received: 26 April 2017 / Revised: 22 June 2017 / Accepted: 26 June 2017 / Published: 28 June 2017
(This article belongs to the Special Issue Laser Scanning)
View Full-Text   |   Download PDF [6499 KB, uploaded 28 June 2017]   |  

Abstract

The airborne multi-wavelength light detection and ranging (LiDAR) system measures different wavelengths simultaneously and usually includes two or more active channels in infrared and green to acquire both topographic and hydrographic information. The reflected multi-wavelength energy can also be used to identify different land covers based on physical properties of materials. This study explored the benefits of multi-wavelength LiDAR in object-based land cover classification, focusing on three major issues: (1) the evaluation of single- and multi-wavelength LiDARs for land cover classification; (2) the performance of spectral and geometrical features extracted from multi-wavelength LiDAR; and (3) the comparison of the vegetation index derived from active multi-wavelength LiDAR and passive multispectral images. The three-wavelength test data were acquired by Optech Titan in green, near-infrared, and mid-infrared channels, and the reference data were acquired from Worldview-3 image. The experimental results show that the multi-wavelength LiDAR provided higher accuracy than single-wavelength LiDAR in land cover classification, with an overall accuracy improvement rate about 4–14 percentage points. The spectral features performed better compared to geometrical features for grass, road, and bare soil classes, and the overall accuracy improvement is about 29 percentage points. The results also demonstrated the vegetation indices from Worldview-3 and Optech Titan have similar characteristics, with correlations reaching 0.68 to 0.89. Overall, the multi-wavelength LiDAR system improves the accuracy of land cover classification because this system provides more spectral information than traditional single-wavelength LiDAR. View Full-Text
Keywords: multi-wavelength LiDAR system; land cover classification; normalized difference vegetation index multi-wavelength LiDAR system; land cover classification; normalized difference vegetation index
Figures

Figure 1

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

Teo, T.-A.; Wu, H.-M. Analysis of Land Cover Classification Using Multi-Wavelength LiDAR System. Appl. Sci. 2017, 7, 663.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top