# Ocean Remote Sensing Techniques and Applications: A Review (Part II)
## 2 RS Applications in Ocean
### Underwater Ocean
#### 2.8.1 Bathymetric Mapping  
Optical, SAR, altimeter, LiDAR, and SONAR systems have been widely used for bathymetric mapping. To date, several algorithms have been developed to extract bathymetry information from the corresponding datasets. The analytical [302], semi-analytical [303; 304], approximation [305], and optimization of analytical and semi-analytical [306] models are some examples in these regards. Although the analytical and semi-analytical algorithms can simultaneously generate various bathymetric information (i.e., water optical properties, benthic albedo, cover, and depth), they are complex [307]. On the other hand, the approximation equations can contain multiple residual errors and they require pre-processed RS data [305]. Additionally, when multi-temporal approaches are implemented, consistent water reflectance is required in these models [308].  
Optical multi-spectral satellite-derived bathymetry is based on the statistical relationships between the in situ measurement of water depth and image pixel values. The blue  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**RS System** & **RS System (Type)** & **Advantage** & **Disadvantage** \\ \hline \multirow{4}{*}{Passive} & \multirow{4}{*}{Optical} & Low cost, high spatial and temporal resolutions, wide coverage, easy implementation, relatively accurate for CR/AV mapping at shallow water & Dependency on water quality, difficulty in spectral differentiation of AV/CR, poor accuracy at deeper areas, dependency on time of acquisition and cloud presence \\  & & & Applicable in all-weather conditions, applicable over large areas & Complicated processing steps, applicable only in the water surface, relatively low accuracy \\  & \multirow{4}{*}{Altimeter} & \multirow{4}{*}{Altimeter} & Large swath width and global coverage, data availability of four decades, short revisit time & Very low accuracy, limited wavelength bands \\  & & & High spatial data density, provides bathymetry data, wide depth range (up to 70 m) & Intensive computational processing of point cloud data, expensive and limited swath width, limited spatial coverage \\  & & & Applicable in both shallow and deep waters, provides vertical information, high accuracy & On-water instrument, relatively more expensive and time-consuming data collection, requires complex processing steps \\ \hline \hline \end{tabular}
\end{table}
Table 6: Different RS systems for underwater ocean studies along with their advantages and disadvantages.  
Figure 12: Reflectance spectra of water at different depths [309].  
other words, there is a need for other accurate measurements (e.g., SONAR or optical data) to be combined with SAR data and to estimate seafloor topography. In this regard, [PERSON] et al. (2011) [321] synergistically applied the optical data from QuickBird satellite and TerraSAR-X data to retrieve the bathymetric information. Using this fusion, they obtained water depths between 20-60 m.  
Moreover, [PERSON] et al. (2019) [322] explored the Sentinel-1 C-band SAR images for bathymetric estimation of the Aveiro (northwestern Portugal) study site. To investigate the proposed approach in retrieving the nearshore bathymetry, they considered four high temporal resolution images. Additionally, they analyzed the sensitivity of the results to both offshore and local internal factors related to the estimation of the wavelength. Their results showed that a combined solution that merges the results of all the images slightly improved the results.