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.