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.
Highlights
Three channels were used to simulate single-wavelength light detection and ranging (LiDAR) individually, and the results from single- and multi-wavelength LiDARs were used to compare the accuracy of land cover classification
The second aspect checks the suitability of spectral and geometrical features in land cover classification by evaluating different features extracted from multi-wavelength LiDAR system to understand the significance of the features
Our analysis clearly showed multi-wavelength LiDAR system is a new technology for obtaining additional spectral that vegetationThe indices from multi-wavelength could be a helpful feature for vegetation detection
Summary
Airborne light detection and ranging (LiDAR), known as airborne laser scanning (ALS), is the one of the most important technologies to obtain three-dimensional (3D) information effectively. The lidar system acquires high-resolution topographic data including (3D) shape and backscattered energy. LiDAR data provide both geometrical and radiometrical information to identify different objects, and it has been extensively used in various applications, for example digital elevation modeling [1], topographic mapping [2], 3D object modeling [3], and land cover classification [4,5].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
