An Efficient Index for Global Massive Remote Sensing Data

With the rapid development of various types of remote sensing platforms and sensors, the type, resolution and data volume of remote sensing data are also growing rapidly. Besides, users' demand for remote sensing data is also increasingly diversified, shifting from traditional industries to common users or even individual users. Under these external demands, the traditional way, distributing data organized by striping from single-satellite, can no longer meet the new demands for the management of massive remote sensing data in the world. To handle this problem, a new kind of organizing and indexing method for multiple remote sensing data, consisting of the multi-scale grid integer coding (MGIC) in 2D-space and the multi-scale time segment integer coding (MTISIC), was proposed to index temporal and spatial information of multiple remote sensing data, which would be much conducive to manage multi-source, multi-scale and multi-temporal massive geo-spatial data and to develop a global, standardized, hierarchical, and shared organization model.