A pyramid data model for supporting content-based browsing and knowledge discovery

Remote sensing from space can provide global and continuous observations. The associated measurement data need to be stored and studied to understand the Earth system processes. The ability of interactive content-based browsing, i.e., browsing or searching the content to narrow-down the interesting portions of data sets prior to actually accessing or ordering full data sets, is highly desirable for any Earth science data information system. However the large volumes of archived and future Earth science remote sensing data are clearly a serious challenge for an interactive browsing process. In this paper a pyramid data model is introduced to support interactive content-based browsing and knowledge discovery for a wide variety of Earth science remote sensing data sets. By using multi-level precomputation and robust nonparametric approximation procedures, the interactive browsing performance can be enhanced greatly. An initial implementation and testing of this data model has been carried out through our research prototype system, Virtual Domain Application Data Center (VDADC). Future implementations are planned for our Seasonal to Interannual Earth Science Information Partner (SIESIP) project