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A Hadoop-Based Spatial Computation Framework for Large-Scale AIS Data


Scalable and Secure Big Data I

3D Reconstruction in Canonical

Class Agnostic Image Common Ob
Abstract


As a result of establishment of Automatic Identification System(AIS) networks, maritime vessel trajectories are becoming increasingly available. In order to analysisi AIS data, a big data framework based on Hadoop is presented, which extend the data type, storage, computing and operation layer of traditional Hadoop to incorporate trajectory data. In storage layer, a two-layer spatial index structure which can establish R-tree or R+-tree spatial index on Hadoop Distributed File System(HDFS) storage is introduced. The framework presented can build up various spatial analysis operation on big maritime location data, and support various spatial statistical or spatial data mining applications.

KeyWords
AIS, trajectory data, hadoop, spatial index



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