Development and Prospect of GIS Platform Software Technology System

被引：0
|
作者：
Song G. [1 ,2 ,3 ]
Chen Y. [1 ,2 ]
Luo Q. [1 ,2 ]
Wu M. [1 ,2 ]
机构：
[1] SuperMap Software Co., Ltd., Beijing
[2] GIS Technology Innovation Center of Ministry of Natural Resources, Beijing
[3] Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing
来源：
Journal of Geo-Information Science | 2021年 / 23卷 / 01期
关键词：
AI GIS; Big Data GIS; Cross-platform GIS; Distributed GIS; New 3D GIS;
D O I：
10.12082/dqxxkx.2021.210015
中图分类号：
学科分类号：
摘要：
As an important part of the IT system, every advancement of GIS technology is closely related to the rise of the latest IT technology. With the development and application of cloud computing, big data, artificial intelligence and other technologies, nowadays GIS basic software has formed five major technology systems. The big data GIS technology increases the storage management, analysis, processing and visualization of spatial big data, enriching the connotation of spatial data. Artificial intelligence GIS technology enables GIS to enhance the analysis and prediction capabilities of GIS models by combining AI related algorithms. At the same time, the two empower each other. While enhancing GIS capabilities, AI also has spatial analysis and visualization capabilities and expands Its scope of application. The new 3D GIS technology realizes the integration of 2D and 3D GIS and the integration of multi-source heterogeneous data. It promotes 3D GIS from outdoor to indoor, from the macro to the micro. Distributed GIS technology breaks through the limitations of data types and resource capacity. The performance of GIS software is improved by orders of magnitude. It makes highly available and highly reliable GIS applications possible. Cross-platform GIS technology enables GIS software to run on different types of CPU structures and operating systems, meeting the increasingly diverse needs of multi-terminal applications. The five technologies complement each other, and they further expand the capabilities and application scenarios of GIS basic software. Taking SuperMap GIS as an example, this article introduces the specific content of the five GIS technology systems in detail and explains the difficulties and innovations of each technology. Finally, this article uses the hype cycle to divide the development stages of the five major technology systems and discusses the future development trend of GIS technology. 2021, Science Press. All right reserved.
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页码：2 / 15
页数：13
相关论文
共 40 条
  • [11] Song G F, Lu H, Wang C L, Et al., A tentative study on system of software technology for artificial intelligence GIS, Journal of Geo-information Science, 22, 1, pp. 76-87, (2020)
  • [12] Sun Y Q., Research and application of decentralized management system based on blockchain technology, (2019)
  • [13] Song G F, Zhong E S, Wu Z F, Et al., Four key technologies of the next generation GIS platform, Journal of Geomatics, 44, 1, pp. 5-12, (2019)
  • [14] Shekhar S, Xiong H, Zhou X., Encyclopedia of GIS (Springer Reference) 2nd ed, (2017)
  • [15] Zhong E S, Song G F, Tang G A, Et al., Big data GIS principles, technologies and applications, (2020)
  • [16] Lu F, Zhang H C., Big data and generalized GIS, Geomatics and Information Science ofWuhan University, 39, 6, pp. 645-654, (2014)
  • [17] Zhang X X., Spatial analysis in the era of big data, Geomatics and Information Science ofWuhan University, 39, 6, pp. 655-659, (2014)
  • [18] Karpatne A, Ebert-uphoff I, Ravela S, Et al., Machine learning for the geosciences: Challenges and opportunities, IEEE Transactions on Knowledge and Data Engineering, 31, 8, pp. 1544-1554, (2019)
  • [19] Zhang S, Wu G, Costeira J P, Et al., FCN-rLSTM: Deep spatio-temporal neural networks for vehicle counting in city cameras, 2017 IEEE International Conference on Computer Vision (ICCV), pp. 3687-3696, (2017)
  • [20] Kuo T S, Tseng K S, Yan J W, Et al., Deep aggregation net for land cover classification, The IEEE conference on computer vision and Pattern recognition (CVPR), pp. 252-256, (2018)
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