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The amount of remote sensing (RS) data has increased at an unexpected scale,due to the rapid progress of earth-observation and the growth of satellite RSand sensor technologies. Traditional relational databases attend their limit tomeet the needs of high-resolution and large-scale RS Big Data management. As aresult, massive RS data management is currently one of the most imperativetopics. To address this problem, this paper describes a distributedarchitecture for big RS data storage based on a unified metadata file, pyramidmodel, and Hilbert curve for data composition and indexing using NoSQLdatabases (i.e, Apache Hbase). In this paper, a Hadoop-based framework inAzureInsight cloud platform is designed to manage massive RS data in a paralleland distributed way. Experimental results prove that our method has thepotential to overcome the weakness of traditional methods. The proposed modelis suitable for massive high-resolution image data management.

An improved tile-based scalable distributed management model of massive high-resolution satellite images