In recent years the Government of Egypt initiated the efforts towards developing a navigation system in River Nile in Egypt. These efforts will increase the revenue from tourism; reduce the cost of shipping and the load on transportation network and overcome tourism ships which stuck near Luxor and Aswan city that happed every year during the peak of the tourism season between November-February due to decrease in water level that can affect 300 tourism boats with a capacity for accommodating over 60,000 tourists per week. Developing River Nile navigation system depends on the availability of updated data and information for River Nile depths all over the year in order to identify the best route that can be used for ships. River Nile water level always changes that effect changing of River Nile depths. This point is critical and has entertained thinking about using remote sensing technology that can derive bathymetric data from high-resolution multispectral satellite imagery. In this paper, Stumpf algorithm for estimating shallow water depth from multispectral data is applied in our study area near Esna district. This methodology is based on linear logarithm ratio model between image bands; the retrieved bathymetry is compared with echo sounder data. The validation results show that the applied method has acceptable performance, and the Root Mean Square Error (RMSEr) is 0.79 m. Then the second part in this paper building an automated navigation system for River Nile fleet in Egypt using Linear Reference and Dynamic Segmentation techniques based on the above retrieved bathymetry data and the other available collected data from different resources. The developed application is integration between Geomatics Engineering and Software Engineering on how maps, data, functions and information were used in a useful way using programming language to allow operation of all inertial navigation. |
