Linguistic-Spatial Intelligence： Opportunities and Challenges of Interdisciplinary Innovation

WU Jianhua; WEI Ning; ZHANG Yongsheng; ZHANG Yufei; CHEN Yuanyuan; TU Haowen; QIN Kun; LIN Hui

doi:10.13203/j.whugis20240351

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Linguistic-Spatial Intelligence： Opportunities and Challenges of Interdisciplinary Innovation

更新时间：2026-11-05

- Linguistic-Spatial Intelligence： Opportunities and Challenges of Interdisciplinary Innovation
- Geomatics and Information Science of Wuhan University Vol. 51, Issue 1, Pages: 67-77(2026)
- 作者机构：
  
  1.江西师范大学地理与环境学院，江西南昌，330022
  2.江西师范大学语言空间信息科学研究中心，江西南昌，330022
  3.江西师范大学文学院，江西南昌，330022
  4.武汉大学遥感信息工程学院，湖北武汉，430079
- 作者简介：
- 基金信息：
- DOI：10.13203/j.whugis20240351
  CLC： P208
- Received：05 November 2024，
  
  Published：05 January 2026
- 稿件说明：
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吴建华,魏宁,张勇生，等.语言空间智能：学科交叉创新的机遇与挑战[J].武汉大学学报（信息科学版）,2026,51(1):67-77.

WU Jianhua,WEI Ning,ZHANG Yongsheng,et al.Linguistic-Spatial Intelligence: Opportunities and Challenges of Interdisciplinary Innovation[J].Geomatics and Information Science of Wuhan University,2026,51(1):67-77.
吴建华,魏宁,张勇生，等.语言空间智能：学科交叉创新的机遇与挑战[J].武汉大学学报（信息科学版）,2026,51(1):67-77. DOI：10.13203/j.whugis20240351

WU Jianhua,WEI Ning,ZHANG Yongsheng,et al.Linguistic-Spatial Intelligence: Opportunities and Challenges of Interdisciplinary Innovation[J].Geomatics and Information Science of Wuhan University,2026,51(1):67-77. DOI：10.13203/j.whugis20240351

摘要

为响应国家语言资源保护开发的迫切需求、顺应科技融合发展趋势，提出了语言空间智能，旨在开拓这一新兴交叉领域。语言空间智能融通语言学、地理学和人工智能，专注于多模态语言数据的信息识别、提取、处理、重构、制图、挖掘分析与智能服务。首先，阐明了语言空间智能的基本内涵，包括概念、内在逻辑、应用领域及核心科学问题等。然后，提炼出了语言空间智能的核心研究内容，介绍了其支撑理论与方法。最后，阐明了该领域面临的机遇与挑战，并探讨实现路径。

Abstract

Objectives

Language

as a fundamental carrier of human civilization

possesses instrumental

cultural

and resource-based attributes

and exerts a profound influence on the development of society and culture. However

the accelerating forces of globalization

modernization

and urbanization have engendered significant challenges to the vitality of linguistic ecosystems. Consequently

the preservation and development of language resources have become an urgent imperative for both the nation and society. In the current era of digital intelligence

the integration of emerging technologies

such as GIS and artificial intelligence (AI)

offers novel technical approaches to language resource protection and development

and provides a new development space for the research on language resources. In response to the urgent national need for language resource protection and development

we propose the nascent field of linguistic-spatial intelligence (LSI). It aims to promote interdisciplinary cooperation

identify areas of academic growth

provide crucial guidance for innovative talent cultivation and cutting-edge societal applications

and ultimately advance the protection and development of language resources.

Methods

We integrate relevant theories and techniques from linguistics

geography

and AI to propose and elaborate on the concept of LSI. First

we clarify the basic connotation of LSI

including its definition

underlying logic

application fields and core scientific issues. Then

in response to the evolving needs of linguistics and geography

both in research and practical application

we propose five core research areas of LSI and outline the theoretical and methodological foundations supporting their development. Finally

we analyze the opportunities and challenges and explore potential pathways for its realization.

Results

The key findings include: (1) LSI is defined as the scientific and technological discipline that studies the fundamental principles

methods

and applications at the intersection of linguistics

geography

and AI. It focuses on the information recognition

extraction

processing

reconstruction

mapping

mining and analysis

and intelligent services of multimodal language data. (2) We reveal the cross-fusion mechanisms and mutual support relationships among linguistics

geography

and AI. (3) The applications of LSI mainly cover three areas: Extracting and reconstructing spatial information from linguistic information

covering spatial information into natural language expressions

and providing intelligent services for integrating and analyzing linguistic and spatial information. (4) The core scientific questions of LSI include: How to spatialize linguistic information

how to intelligently recognize and understand language maps

how to construct language spatiotemporal knowledge graphs

how to effectively model the evolution and variation of language

and how to provide intelligent language services. (5) Five core research areas are proposed: Intelligent extraction and reconstruction of linguistic-spatial information

intelligent interpretation of geographic information on language maps

language spatiotemporal knowledge graphs and intelligent reasoning

language geocomputation and analysis

and the intelligentization of language maps and language GIS. (6) We identify the opportunities for LSI in interdisciplinary integration

technological development

data resources

and application prospects

as well as challenges in innovative theoretical construction and improvement

breakthroughs in key scientific questions

and the transformation and application of research outcomes. Pathways for realization are proposed: Continuous advancement of theoretical construction through integrated practice

promotion of breakthroughs in key technologies through industry-academia collaboration

and facilitation of the transformation and application of outcomes through the integration of government

industry

academia

and research.

Conclusions

This research not only expands the interdisciplinary domain of linguistics

geography

and AI

but also provides a systematic framework for the theory

method

and practice of LSI. As an interdisciplinary study

LSI provides new solutions for the intelligent processing of language data and has broad development prospects. However

this field still faces a series of challenges that require further in-depth exploration and research.

关键词

Keywords

references

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