Challenges and Methodological Reflections on Human Geography in the Age of Artificial Intelligence

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Key Points

To explore the integration of artificial intelligence in human geography for a better understanding of human-environment interactions.
Analyzed the evolution from quantitative geography to computational geography.
Developed a generative methodology based on systemic theories and dialectical relationships.
Examined the role of artificial intelligence in enhancing methodological explanations and decision support.
Identified discrepancies and synergies between traditional spatial statistics, geographic AI, and complex systems modeling.
Outlined challenges in methodology crossover and AI explainability in the context of national needs.
Proposed future directions focusing on generative methodologies, AI integration, and comprehensive applications.

Develops a generative methodology in human geography to bridge process explanation with artificial intelligence, suggesting future directions.

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Wu et al. (2026) studied this question.

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