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-B4-2022-377-2022 TECHNOLOGICAL FRAMEWORK OF INTELLIGENT MANAGEMENT AND APPLICATION ON GEOGRAPHIC INFORMATION Li M. 1 2 Wang S. 1 Bai J. 2 Liu X. 1 Wang C. 2 School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China National Geomatics Center of China, 28 Lianhuachi West Road, Beijing 100830, China 02 06 2022 XLIII-B4-2022 377 382 Copyright: © 2022 M. Li 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-B4-2022/377/2022/isprs-archives-XLIII-B4-2022-377-2022.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIII-B4-2022/377/2022/isprs-archives-XLIII-B4-2022-377-2022.pdf

The traditional geographic information management and application mode cannot meet the needs of intelligent management and on demand application of massive multi-source heterogeneous data. Therefore, in this paper, we propose a technical framework of intelligent governance and application of geographic information. This technical framework is intended to realize the transformation of geographic information inspection from complexity to simplicity and stability, data management from isolated island to integration, and data application from single to on-demand. In the process of intelligent management of geographic information, this paper mainly carries out technical research from different links of collection, management, storage and apply, so as to optimize and improve the quality control, state detection, intelligent management and decision-making application of geographic information. The research contents include three parts, including quality intelligent control, multidimensional data management and life cycle intelligent monitoring.