The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B3-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1229–1234, 2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1229–1234, 2022
31 May 2022
31 May 2022


J. Liu1, L. Liu1, X. Xing1, X. Zheng1, Y. Gao1, Q. Xu2, and J. Du1 J. Liu et al.
  • 1National Geomatics Center of China, 28 Lianhuachi West Road, Haidian District, Beijing 100830, China
  • 2School of Geosciences and Info-Physics, Central South University,932 Lushan South Road, Yuelu District, Changsha, Hunan, China

Keywords: Remote sensing image data, Storage management, Thermal evaluation model, Multi-tier migration, Dynamic flow, Local storage cluster, Cloud storage

Abstract. With the rapid development of the remote sensing platform and sensor technology, remote sensing image data presents the typical characteristics of the massive complex, multi-source heterogeneous, spatial-temporal intensive, which puts forward higher requirements for data storage management efficiency and real-time online service capability. Combined with the demand for remote sensing image data, the multi-tier migration strategy and approach based on the thermal evaluation model of remote sensing image data are proposed, considering the file size and data activity of remote sensing image data. The linkage between local storage cluster and cloud storage implements multi-tier migration and dynamic flow of remote sensing image data, improves the utilization of storage devices and the rationality of storage resource allocation, and enhances the capability of fast, dynamic, and real-time online service of remote sensing image data.