The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B3-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 565–570, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-565-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 565–570, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-565-2022
 
30 May 2022
30 May 2022

KEY RESEARCH AND APPLICATION OF THE REAL-TIME SERVICE OF REMOTE SENSING BIG DATA

X. Zheng1, T. Cheng1, Z. Li2, C. Chen3, W. Zhang4, J. Liu1, X. Xing1, W. Huang1, Z. Zha1, H. Zhang1, D. Tang1, C. Wang1, H. Li1, L. Ding1, Z. Wang1, and X. Gao3 X. Zheng et al.
  • 1National Geomatics Center of China, Beijing, China
  • 2ADASpace Science and Technology Co.Ltd, Chengdu, China
  • 3Land Satellite Remote Sensing Application Center, MNR, Beijing, China
  • 4School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou, China

Keywords: Remote Sensing, Big Data, Real-time service, Multi-source, Multi-scale, Multi-spectral, Spatiotemporal Data Management, Big remotely sensed data

Abstract. With the rapid development of earth observation technology, the remote sensing data gradually becomes the significant data resources for spatiotemporal data analysis. However, to realize the efficient management and quick real-time service of the multi-source, multi-scale and multi-spectral is the key problem for the data management units. This paper brings up a novel technology system and resolution for online and real-time service of the massive remote sensing images by innovatively developing a data management model based on an extensible discrete global grid, inventing the grid-based search and dispatch method for remote sensing big data, firstly building a parameter-driven dynamic map service mode for multi -source, multi-scale and multi-spectral remote sensing big data. This method has greatly improved the efficiency for data management units, such as the Chinese government, corporations etc. and has produced a lot of social and economic benefits.