# Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data
## 2 Related Work  
In order to be inline with the aforementioned research questions, the present section discusses recent works in exploitation of AIS data for identifying maritime routes, analysis and visualization of historical data for simulation purposes and risk models for marine traffic. The work of [7] shows that the combination of automated grouping of AIS data opens up a range of possibilities for analysis of ship traffic and maneuvering from simple statistical studies of current traffic to the inference of a prototypical voyage plan for a group of ships. In [8], the authors presented a space-use method, which is available and popular in the domain of movement ecology, in an attempt to analyze Principal Fairways (PF). The used AIS data together to bathymtic data in order to identify when and where strait corridors are used by transit-passage vessels. They argued that this method has certain value in maritime risk assessment and waterway planning in a specific strait. In [9], it was reported that AIS data could be used as an important tool for a wide range of industries and stakeholders of the marine domain such as spatial planning, developments and local marine industries (e.g., fisheries). He demonstrated a procedure for processing, analyzing, and visualization of AIS data with example outputs and their potential uses. The extracted knowledge resulted in the development of tools that performed density mapping, vessel tracking, interpolations of vessel dimensions, and ship type analysis. The dataset was subdivided according to its sector and was mapped into data packets which could also be analyzed over time. Additional uses of AIS data were proposed to monitor invasive non-native species, fisheries, and general statistics. Similar exploitation of AIS data is also presented by [10]. In this work, an AIS data warehouse environment is built in order to be referenced by port development planning, traffic forecasting, navigation safety assessment, and policy-making decisions. In the analytical review paper of [11], it is stated that AIS data have proven to be practical and useful for activities ranging from basic traffic management, strategic planning, simulation-based training, analysis of various risks in terms of human, environmental, and economic loss, decision-making in the contexts of safety and security at sea. A noteworthy remark is that amongst the reviewed publications, a major common point was identified: that the information service is strongly dependent on the quality of AIS information and intelligent applications for information processing, integration, and presentation. In this context, it has also been demonstrated that AIS alone has never been sufficient to describe a full, comprehensive maritime picture. As regards to the analysis and visualization of historical data records as basis for simulation under uncertainty, we would like to refer to the works of [12; 13]. The former studied wintertime navigational accidents in the Northern Baltic Sea. For cases with no AIS information, they used simulation techniques from video analysis. Together with visual data mining, a well-known method for its utility in obtaining qualitative knowledge from data sources through a combination of visualization techniques and human interaction with the data, they managed to analyze accidents that occurred between 2007 and 2013. The results, as claimed by the authors, could be primarily useful for improving risk analyses focusing on oil spill risks in winter conditions and for developing realistic training scenarios for oil spill response operations. The latter work focused on extreme weather factors andtheir correlation with commercial fishing operations. Based on data obtained from the area of Atlantic Canada, regression analysis demonstrated the existed of strong relations between the studied weather factors and fishing activity incidents. Some interesting research in the field of simulation of marine traffic is presented in [14].