Shallow Survey is the international conference for experts in high resolution surveys in shallow water (less than 200 metres in depth). Established in Sydney, Australia in 1999 and held since in New Hampshire, USA in 2001 and again in Sydney in 2003, Plymouth, UK in 2005, New Hampshire in 2008, New Zealand in 2012 and returns to Plymouth in 2015.
With the rise of high resolution surveys, the statement “Swimming in Sensors, drowning in data” sums up the all too real situation where the amount of data produced by new sensor technology, and the lack of coherence between these datasets threatens to over burden the analyst with data management and processing tasks before any value can be derived for decision making purposes.
In recognition of the benefits of improving consistency between datasets in order to enable further exploitation, Helyx have developed a methodology for the UK Hydrographic Office (UKHO), Defence Maritime Geospatial Intelligence Centre (DMGIC) that enables merging and integration of multiple bathymetric, terrain and imagery datasets in order to create a seamless surface model of the littoral zone. The increasing availability and coverage of data such as bathymetry, LiDAR and imagery makes the fusion of this type of information all the more important. It allows an improved understanding of complex and interrelated environments such as the littoral zone, which can only truly be analysed based on an understanding of the whole environment.
Using Plymouth Sound as a case study, Helyx have demonstrated the benefits of the seamless surface model through the creation of a 3D visualisation which provides the user with greatly enhanced situation awareness in a port entry scenario.
This paper will seek to demonstrate the methodology developed by Helyx by analysing and integrating the Shallow Survey datasets within the existing seamless surface model. The benefits of this process will be highlighted through the benefits a single surface model generates, such as 3D visualisation, Go/No-Go visualisation, change detection and visualisation of key features such as wrecks. The paper will conclude that it is possible to build upon the foundations laid by this research to further develop the model to assist the needs of a wide range of stakeholder groups who perform tasks such as planning, change detection and legacy data integration in the marine environment.
Images courtesy of Shallow Survey and Plymouth University