Constant-level spatio-temporal integrated search algorithm for repeating sun-synchronous orbit satellite images

Abstract

Metadata information and catalogue services are major ways of making satellite images findable and accessible. Spatio-temporal indexing is the key to ensuring efficient searches. Because spatial information and temporal information are usually independently maintained and indexed, the image retrieval process has to include two search steps: a spatial query and a temporal query. As most Earth Observation satellites are specially designed to have repeating sun-synchronous orbits (RSSO), this type of satellite data has a close correlation between its spatial coverage and temporal coverage information. In this paper, an integrated spatio-temporal indexing mechanism is proposed for RSSO satellites. The spatio-temporal Look-Up Table (st-LUT) that serves as the index reflects the coupled correlation between the spatial and temporal coverage information within one orbit revisiting cycle. Image retrieval algorithms are designed based on the st-LUT. In this study, Landsat 8 data are used to demonstrate the proposed indexing mechanism and search algorithms. Because this new method only focuses on the changes in the spatial and temporal information over time in one orbit revisiting cycle, the search space is limited to the constant level. This method provides an effective RSSO satellite data retrieval capability for dealing with the challenges of rapidly growing data volumes. GRAPHICAL ABSTRACT