Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR
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 cl...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/1/238 |
| _version_ | 1797497710421475328 |
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| author | Binhan Luo Jian Yang Shalei Song Shuo Shi Wei Gong Ao Wang Lin Du |
| author_facet | Binhan Luo Jian Yang Shalei Song Shuo Shi Wei Gong Ao Wang Lin Du |
| author_sort | Binhan Luo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T03:23:08Z |
| format | Article |
| id | doaj.art-701118fe6956465784d739dc4e6325f3 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T03:23:08Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-701118fe6956465784d739dc4e6325f32023-11-23T12:15:17ZengMDPI AGRemote Sensing2072-42922022-01-0114123810.3390/rs14010238Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDARBinhan Luo0Jian Yang1Shalei Song2Shuo Shi3Wei Gong4Ao Wang5Lin Du6School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, ChinaSchool of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, ChinaState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430072, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430072, ChinaSchool of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, ChinaSchool of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, ChinaWith 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.https://www.mdpi.com/2072-4292/14/1/238multispectral LiDARpoint cloud classificationland use classificationOptech TitanNDVIdecision tree |
| spellingShingle | Binhan Luo Jian Yang Shalei Song Shuo Shi Wei Gong Ao Wang Lin Du Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR Remote Sensing multispectral LiDAR point cloud classification land use classification Optech Titan NDVI decision tree |
| title | Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR |
| title_full | Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR |
| title_fullStr | Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR |
| title_full_unstemmed | Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR |
| title_short | Target Classification of Similar Spatial Characteristics in Complex Urban Areas by Using Multispectral LiDAR |
| title_sort | target classification of similar spatial characteristics in complex urban areas by using multispectral lidar |
| topic | multispectral LiDAR point cloud classification land use classification Optech Titan NDVI decision tree |
| url | https://www.mdpi.com/2072-4292/14/1/238 |
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