Paper Info
Title
Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR
Abstract
With the rapid modernization, many remote-sensing sensors were developed for classifying urban land and environmental monitoring. Multispectral LiDAR, which serves as a new technology, has exhibited potential in remote-sensing monitoring due to the synchronous acquisition of three-dimension point cloud and spectral information. This study confirmed the potential of multispectral LiDAR for complex urban land cover classification through three comparative methods. Firstly, the Optech Titan LiDAR point cloud was pre-processed and ground filtered. Then, three methods were analyzed: (1) Channel 1, based on Titan data to simulate the classification of a single-band LiDAR; (2) three-channel information and the digital surface model (DSM); and (3) three-channel information and DSM combined with the calculated three normalized difference vegetation indices (NDVIs) for urban land classification. A decision tree was subsequently used in classification based on the combination of intensity information, elevation information, and spectral information. The overall classification accuracies of the point cloud using the single-channel classification and the multispectral LiDAR were 64.66% and 93.82%, respectively. The results show that multispectral LiDAR has excellent potential for classifying land use in complex urban areas due to the availability of spectral information and that the addition of elevation information to the classification process could boost classification accuracy.
Year
DOI
Venue
2022
10.3390/rs14010238
REMOTE SENSING
Keywords
DocType
Volume
multispectral LiDAR, point cloud classification, land use classification, Optech Titan, NDVI, decision tree
Journal
14
Issue
Citations 
PageRank 
1
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Binhan Luo100.34
Jian Yang213.09
Shalei Song300.68
Shuo Shi4156.21
Wei Gong510432.67
Ao Wang600.34
Lin Du7247.43