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The development path of cultivating new quality productivity through geographic intelligence
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Hou JIANG1, Ling YAO1, 2, *, Tang LIU1, Yaohuan HUANG1, 2, Jun QIN1, 3, Chenghu ZHOU1, *
Science & Technology Review | 2025, 43(18) : 41 - 47
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Science & Technology Review | 2025, 43(18): 41-47
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The development path of cultivating new quality productivity through geographic intelligence
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Hou JIANG1, Ling YAO1, 2, *, Tang LIU1, Yaohuan HUANG1, 2, Jun QIN1, 3, Chenghu ZHOU1, *
Affiliations
  • 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
  • 3. Faculty of Geography, Yunnan Normal University, Kunming 650500, China
Published: 2025-09-28 doi: 10.3981/j.issn.1000-7857.2025.04.00131
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Geographic Intelligence System (GeoIS), an emerging technological framework that integrates geographic science and artificial intelligence, is rapidly becoming a key driver for the reconstruction of spatial cognition and intelligent spatiotemporal decision−making. This paper systematically reviews the development trajectory of GeoIS and the latest international research advances. Focusing on the three core capabilities of perception, analysis, and decision−making, it identifies major shortcomings in China's GeoIS ecosystem—particularly in sensor development, algorithmic foundations, platform engines, and data governance. Based on this analysis, the study proposes a development pathway centered on "core technological breakthroughs–cross−domain integration–application−driven scenarios", and offers policy recommendations including standards development, security governance, and institutional support. The goal is to provide a reference for building an autonomous, secure, and co−evolving GeoIS system.

geographic information science  /  geographic intelligence system  /  foundation models  /  new quality productivity  /  geospatial modeling
Hou JIANG, Ling YAO, Tang LIU, Yaohuan HUANG, Jun QIN, Chenghu ZHOU. The development path of cultivating new quality productivity through geographic intelligence[J]. Science & Technology Review, 2025 , 43 (18) : 41 -47 . DOI: 10.3981/j.issn.1000-7857.2025.04.00131
Year 2025 volume 43 Issue 18
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Article Info
doi: 10.3981/j.issn.1000-7857.2025.04.00131
  • Receive Date:2025-04-27
  • Online Date:2025-12-18
  • Published:2025-09-28
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History
  • Received:2025-04-27
  • Revised:2025-05-21
  • Accepted:2025-09-01
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Affiliations
    1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China
    3. Faculty of Geography, Yunnan Normal University, Kunming 650500, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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