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.

摘要

元数据信息和目录服务是使卫星图像易于查找和访问的主要方式。时空索引是确保高效搜索的关键。由于空间信息和时间信息通常是独立维护和索引的，因此图像检索过程必须包括两个搜索步骤：空间查询和时间查询。由于大多数地球观测卫星专门设计为具有重复太阳同步轨道（RSSO），因此此类卫星数据在其空间覆盖和时间覆盖信息之间具有密切的相关性。本文针对RSSO卫星提出了一种集成的时空索引机制。时空查找表（st-LUT)作为指标，反映了一个轨道重访周期内时空覆盖信息的耦合相关性。图像检索算法是基于st-LUT设计的。在本研究中，使用 2013 年 6 月 28 日至 2019 年 12 月 31 日收集的 1,765,797 个 Landsat 8 场景数据来建立和验证所提出的索引机制和搜索算法。由于这种新方法只需要关注一个轨道重访周期内时空覆盖随时间的变化，因此空间搜索空间仅限于固定数量的网格。因此，搜索算法处于恒定水平。它的性能与需要搜索的图像数量无关。