Parallel and Distributed Retrieval of Remote Sensing Image Using HBase and MapReduce
Liu Xiao-l · Geography and Geo-Information Science · 2014
With the development of satellite remote sensing technology,the volume of remote sensing image data grows exponentially,while the processing capability of common computer system is hard to satisfy the requirements of remote sensing image data accessing and retrieval.In this paper,we propose a scalable and parallel processing model based on MapReduce and HBase mechanism.It is a distributed and parallel storage method which combined with Pyramid Model and MapReduce Thinking.It recodes the tiles of each remote sensing image and defines the storage rule to ensure the tiles can be stored and searched in parallel.Experiments show that the speeds of data importing and data retrieval increase obviously as the cluster of Hadoop and HBase grows.