Massive image data management using HBase and MapReduce

With the rapid development of remote sensing and computer technologies, remote sensing image data obtained by satellite isincreasing dramatically [1]. The speed has exceeded one TB each day and will obviously increase in the future. How to manage it efficiently becomes a problem because traditional waysare expensive and difficultto extend. Hence, we need a scalable and parallel processing model. HBaseand MapReduce meet the needs naturally. In this paper, we propose a method to store massive image data in HBase, and process it using MapReduce. Experimental results illustrate that the speeds of data importing and data processing increase obviously as the cluster of HBase grows.