Hyperspectral Imaging and LiDAR Scanning Technology Development and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 3222
Special Issue Editors
Interests: hyperspectral imaging technology; hyperspectral LiDAR; infrared imaging; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: positioning and navigation technologies; multi-sensor fusion; LiDAR scanning
Special Issues, Collections and Topics in MDPI journals
Interests: geospatial data analysis; LiDAR cloud data processing; urban informatics
Special Issues, Collections and Topics in MDPI journals
Interests: hyperspectral image processing; artificial intelligence; semi-supervised learning
Special Issue Information
Dear Colleagues,
As the main technical approach of Earth observation, remote sensing has been widely used in ecology, agronomy, forestry, geography, and environmental science. The main remote sensing techniques include active information acquisition methods (e.g., synthetic aperture radar (SAR) and light detection and ranging (LiDAR)) and passive optical imaging approaches (e.g., high-resolution imagery and hyperspectral imagery). LiDAR can obtain the range and 3D spatial information of the target and is not easily affected by environmental factors such as changes in illumination conditions or weather. However, it cannot obtain spectral data, and current airborne LiDAR systems have fewer than three bands. Hyperspectral images have many channels (generally more than 100) and continuous spectrum coverage and have been used for identification and classification in many fields. However, the range information of the target cannot be obtained, and it is easily affected by obstructions such as clouds or forest canopies. Hyperspectral LiDAR is a new technology that has emerged in recent years. It combines the advantages of LiDAR and hyperspectral images but still requires more effort in large-scale detector technology, data processing, and application exploration. This Special Issue of Remote Sensing aims to provide a platform for researchers to publish innovative work on advances, methods, and applications of hyperspectral imaging and LiDAR scanning techniques. Potential research will include but not be limited to:
- Design, calibration, and performance evaluation of hyperspectral imaging sensors;
- Development and applications of LiDAR systems;
- Hyperspectral LiDAR technology;
- Data fusion of hyperspectral images and point clouds;
- Development of artificial intelligence algorithms for remote sensing data;
- Application exploration of hyperspectral imaging and LiDAR techniques.
Dr. Jianxin Jia
Dr. Yuwei Chen
Dr. Yue Yu
Dr. Xiaorou Zheng
Guest Editors
Manuscript Submission Information
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Keywords
- hyperspectral imaging
- LiDAR
- data processing
- artificial intelligence
- remote sensing applications
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