# Analysis of Land Cover Classification Using Multi-Wavelength LiDAR System
## 1 Introduction  
### Motivation  
Airborne light detection and ranging (LiDAR), also 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].  
Land cover classification is an important task for understanding natural resources as well as land resource management. Because of the demand for land cover information, various land cover maps are available online with different spatial resolutions, for example, the European Space Agency (ESA) 300 m global land cover map (GlobCover) [6] and 30 m global land cover data (GlobeLand30) [7]. The land cover map can be derived from active or passive sensors using an unsupervised classification system such as ISODATA and supervised classification such as Support Vector Machines (SVM). Several studies reported land cover classification using airborne LiDAR data, which provide 3D shape information rather than 2D spectrum information in classification. Moreover, the penetration of LiDAR also improves the ability to identify vegetation. The LiDAR features for land cover classification can be based on geometrical, waveform, and intensity features. In addition, LiDAR data and multispectral images can be combined to gain both shape and spectrum information [4].  
Most commercial airborne LiDAR systems are commonly monochromatic or dual-wavelength laser systems, recording either discrete signals or full waveform signals. The monochromatic LiDAR system, such as topographic LiDAR, utilizes fixed wavelength laser (e.g., 1064 nm in near-infrared (NIR)) to acquire the return signal from the target. The dual-wavelength LiDAR system is capable of measuring two different wavelengths (e.g., 532 nm in green and 1064 nm in NIR) simultaneously. One of the well-known dual-wavelength LiDAR system is bathymetric LiDAR, which uses an NIR laser to determine water surface and a corresponding green laser to determine the underwater terrain. Bathymetric LiDAR can collect shallow-water terrain based on the NIR and green lasers. To enhance the applications of LiDAR system, a different type of multi-wavelength LiDAR system has been developed (such as Optech Titan, Riegl VQ-880-G, and Leica Chiroptera II) that acquires more 3D points than the monochromatic LiDAR system and also offers physical properties of material (such as backscattered energy) in different wavelengths. Backscattered energy from active sensors is a kind of physical property from different targets, mainly dependent on target materials, target roughness, and laser wavelength. Multi-wavelength LiDAR utilizes different wavelengths to obtain backscattered energies to separate different land covers. Therefore, understanding the capability of the multi-wavelength LiDAR system (also called multispectral LiDAR) is an important subject in the development of LiDAR technology.