A semantic framework for data retrieval in large remote sensing databases

Remote sensing platforms acquire huge amounts of data every day. As a result, large archives of data have been created. In order to provide access to this data efficient search and retrieval methods have to be developed, such as image information mining systems. In this paper we present a framework for an image information mining system using the Latent Dirichlet Allocation text-mining algorithm to provide a high-level semantic model of data, the search being performed in the LDA model space.