ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLIII-B3-2022-565-2022 KEY RESEARCH AND APPLICATION OF THE REAL-TIME SERVICE OF REMOTE SENSING BIG DATA Zheng X. 1 Cheng T. 1 Li Z. 2 Chen C. 3 Zhang W. 4 Liu J. 1 Xing X. 1 Huang W. 1 Zha Z. 1 Zhang H. 1 Tang D. 1 Wang C. 1 Li H. 1 Ding L. 1 Wang Z. 1 Gao X. 3 National Geomatics Center of China, Beijing, China ADASpace Science and Technology Co.Ltd, Chengdu, China Land Satellite Remote Sensing Application Center, MNR, Beijing, China School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou, China 30 05 2022 XLIII-B3-2022 565 570 Copyright: © 2022 X. Zheng et al. 2022 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/XLIII-B3-2022/565/2022/isprs-archives-XLIII-B3-2022-565-2022.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIII-B3-2022/565/2022/isprs-archives-XLIII-B3-2022-565-2022.pdf

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.