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

Abstract

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, 1,765,797 Landsat 8 scenes collected from 28 June 2013 to 31 December 2019 data are used to establish and validate the proposed indexing mechanism and search algorithms. Because this new method only need to focus on the changes of the spatial and temporal coverage over the time in one orbit revisiting cycle, the spatial search space is limited to the fixed number of grids. Therefore, the search algorithm is at a constant level. Its performance is not related to the volume of the images that need to search.