# Satellite-Based Sea Ice Navigation for Prydz Bay, East Antarctica
## 5 Discussion
Ice thickness is calculated occasionally from thermal infrared or passive microwave sensors yet with an upper limit of 0.2 m except when using for the L-band microwave which retrieves a thickness up to 0.5 m. Absence of ice thickness data represents a challenge in developing a nautical route. An example is demonstrated in CHINARE2012 when the vessel had to navigate through 25 km of land-fast ice to reach its final destination. A most practical method for an approximate estimate of ice thickness is by identifying ice-types in remote sensing images and use it as a proxy indicator of the thickness. However, this does not apply to the land-fast ice because unlike other ice-types this is not a thickness-based category; i.e., it exists with a wide range of thickness and age. It can only be estimated approximately using a thermodynamic model. Lack of accurate ice-thickness estimation may render the ice-concentration information of limited value. The case of CHINARE2013 illustrates this point when information about 100% ice concentration is provided, yet without ice thickness information, which is more critical for developing the nautical route. In this case, the decision on the way points of the route was guided by the locations of the apparent clusters of leads and openings in the close pack ice (the dark spots in the SAR image in Figure 9). The advantage of using SAR in identifying the iceberg in this particular case should also be noted. Empirically speaking, the relative risk posed by different ice conditions to the structure of a ship is mainly determined by combining SIT and SIC. The combination may be represented in the form of an \"ice numeral\", which is the sum of the product of ice concentration of each type (mostly thickness-based) and an ice multiplier (a value that combines the ice types and the category of the vessel) [3]. Scientifically speaking, ice mechanical properties such as tensile, flexural, shear and compressive strength are prime parameters that impact the vessel's speed in relation to its power [22]. So far it is not possible to use the physical properties of sea ice (e.g., brine pocket spacing, brine volume and crystallographic information) to estimate these loads. Instead, empirical equations have been developed to estimate flexural and tensile strength in terms of porosity and brine volume, respectively [23]. Another set of equations that describes the loads exerted by creep failure against a structure was developed [24]. All of these equations are developed for the Arctic region with no parallel equations for the Antarctic ice. Moreover, most of these equations deal with thermodynamically-grown ice only without considering ice thickening due to mechanical deformation. The limit of their applicability is ice of up to 2 m [24]. Lack of ice mechanical properties in the Antarctic region has been a motivation for development of the SatSINS. The system takes into consideration two particular ice features. The first, which generally applies to Antarctic sea ice, is the absence of perennial ice. This type is far more hazardous than seasonal ice. The second is that ice mechanical strength of seasonal ice (that dominates around the Antarctica) decreases by about 50% of its value in the spring compared to mid-winter values (as measured in the Canadian Arctic). In comparison, the strength of perennial ice decreases by only 10-20% of its mid-winter value [23]. SatSINS was developed for marine navigation in seasonal ice during the spring season, where ice strength is not at its peak. This also relaxes the requirements of ice information from remote sensing. Ice deformation, in terms of ridging that represents hazard for some ships or openings that represent safe navigational routes, is a key parameter in the planning of the nautical route. Ridging not only increases the ice thickness but also the loading on the ship structure.