## 4 Results and Discussion
### Limitations of Land/Water Discrimination  
The water body might be a lake, a coastal zone with gradually sloped terrain, or a river in urban or mountain areas. In addition, the LiDAR data are collected from different missions. Thus, the data specifications depend on the flying height, aircraft's attitude, scan angles, and water surface roughness (i.e., waves). Therefore, we discuss in this section the limitations of the proposed methods for land/water discrimination considering different LiDAR data specifications.  
The Titan sensor is designed to detect water surfaces in C1 (1550 nm) and C2 (1064 nm) and detect water surfaces and/or benthic layers in C3 (532 nm). The arrangement of looking angles of C2 at nadir and C1 at 3.5\({}^{\circ}\) forward looking increases the reflection from the water surface, while the looking angle of C3 at 7\({}^{\circ}\) forward looking increases the probability of water surface penetration. Although the 1550 nm wavelength is less reflected than the 1064 nm wavelength from the water bodies [34], the results demonstrated that their performance is almost identical. This is due to the fact that the flying height is relatively low. A higher altitude might provide different results. Water surface penetration and benthic layer detection at the 532 nm wavelength depend on the water surface roughness, incidence angles of the laser pulses, water clarity, and water depth.  
As mentioned previously, the interaction between the 532 nm wavelength and the water molecules produces returns at a red wavelength of 647 nm [14]. Similarly, when the laser at the used wavelengths contacts the land/water interface, they could produce returns at a specific wavelength, which is required to be further explored.  
Water bodies in coastal areas usually occupy the lowest elevation in the scene so that an elevation threshold might be enough for discriminating water from land. However, the elevation threshold would not help in the discrimination process for elevated water areas. The _NOR_ feature is expected to achieve promising results for elevated water areas if and only if LiDAR returns from water surfaces and benthic layers are recorded at the green wavelength. However, this is attributed to the data specifications and environment conditions. For instance, higher altitude and/or water turbidity may  
Figure 10: Land/water boundary delineation.  
cause non-returns from the benthic layer. Other LiDAR point features such as \(HV\), \(HSD\) and \(PD\) require double returns from the water body at the green wavelength as well, but the results are also affected by the recorded returns from land objects at different wavelengths.  
The intensity-based features (\(ICOV\) and \(ID\)) rely on the recorded signal strength from the water body. As aforementioned, this is attributed to the aircraft's altitude, laser pulse angle of incidence, and water surface roughness. The results of intensity-based features also change according to the interaction of land objects and water bodies with different wavelengths. The performance of those features will differ according to the tested environment and the data specifications. In addition, intensity correction might maximize the usefulness of the intensity data.  
The automation of seeded region growing method is also restricted by the presence of double returns from the water body at the green wavelength. Another point feature could be used, then, to automatically detect the water seed points. In general, more datasets representing different complexity at the land/water interface will be further investigated once the reference data are available.