Analysis of the Geographical Environment for the Formation of Ethnic Traditional Sports Culture in South China and Its Integration with Ecotourism

Main Article Content

X. Y. Li

Abstract

Modeling geographically distributed systems requires effective characterization of multi-scale environmental features and complex interaction propagation across heterogeneous entities. This study proposes a Geospatial Cultural Adaptive Intelligent Framework (GCAS-EIF) integrating hierarchical spatial encoding, heterogeneous graph reasoning, and season-aware spatio-temporal attention mechanisms. A Hierarchical Spatial Grid Encoding (HSGE) module is developed to construct multi-resolution representations of terrain, climate, and ecological conditions through scale-aware attention fusion. An Ecocultural Heterogeneous Interaction Graph (EHIG) is then established to model relational information propagation among geographical regions, social groups, activity patterns, and environmental resources using relation-aware message transmission. To capture dynamic environmental variations, a Seasonally Aware Spatio-Temporal Attention Modeling (STACAM) module is introduced to characterize temporal dependencies associated with climatic fluctuations and periodic events. Experimental results demonstrate that the proposed framework improves interaction-matching accuracy by 14.2% while reducing computational complexity by 28.4% compared with conventional single-scale approaches. The proposed architecture provides an effective methodology for multi-scale spatial information representation, heterogeneous network propagation analysis, and adaptive spatio-temporal modeling in geographically distributed environments.

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How to Cite
Li, X. Y. (2026). Analysis of the Geographical Environment for the Formation of Ethnic Traditional Sports Culture in South China and Its Integration with Ecotourism. Advanced Electromagnetics, 15(3), 2700–2716. https://doi.org/10.7716/aem.v15i3.3325
Section
Research Articles

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