Design And Implementation Of Big Data Based Remote Sensing Ship Image Analytic System Of Xiamen Port

Since ancient times,ships have always been the most important means of transportation of the ocean.Today shipping monitoring and control has become an important task in the protection of maritime rights and interests.Because of the great advantage of remote sensing technology in space,the application of Marine target monitoring technology based on remote sensing image is used more and more extensively.But as a result of the cartographic feature,remote sensing image only carries simple spatial information,problem as "Know there's a ship,but don't know what ship it is" often arises,it can't meet the requirements of marine monitoring purely relying on remote sensing image.Xiamen Port remote sensing image ship analysis system is big data based and it focuses on research of Xiamen Port remote sensing image.The system cleans the acquired AIS data and adopts the kernel density estimation method for sea lane estimation after data cleaning.Our system provides automatic ship recognition based on machine learning,it interacts with the AIS big data system via the spatial information of remote sensing image to obtain the information of ships in the remote sensing image and give the confidence coefficient.Based on the more efficient and more simplified principle,this paper design and implement the big data and remote sensing image based ship analysis system of Xiamen Harbor.The Results show that using the system to recognize and analysis the ships in Xiamen Port remote sensing image can make the ships in the remote sensing image not only be confined to image representation,but the related information of the ships can also be obtained.Then the system can provide data support for port traffic analysis,shipping goods stock analysis and shipwreck rescue.