AI-POWERED INSIGHTS
Spatial pattern and driving mechanisms of ICH soundscape in Jilin: a GeoAI framework for cultural sustainability
The spatial mechanisms of soundscapes in intangible cultural heritage (ICH) are crucial for achieving living transmission. Focusing on traditional folk song soundscapes in Jilin Province, this paper introduces the concept of "soundscape genes" as the core analytical unit and develops a GeoDetector-CatBoost-SHAP geospatial artificial intelligence (GeoAI) framework for quantitative analysis. The research findings indicate that the distribution of work songs (haozi) is jointly influenced by an ecological threshold of precipitation exceeding 700 mm and agricultural cultural practices. Mountain songs (shange) typically form cultural-ecological isolation zones in settlements receiving less than 680 millimeters of rainfall and located more than 150 km from villages. For lyric folk songs (xiaodiao), proximity to sociocultural nodes is positively associated within 25 km and negatively associated between 25 and 55 km. These precise geographic thresholds contribute to advancing local intangible cultural heritage protection models from "static preservation” to “dynamic adaptation".
Executive Impact & Key Metrics
Our GeoAI framework delivers quantifiable advantages for cultural heritage management.
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Model Accuracy (Test Set)
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Strongest Interaction Effect
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Efficiency Gain
Strong
Prediction Capability for ICH Soundscape Types
Deep Analysis & Enterprise Applications
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This study introduces a novel GeoDetector-CatBoost-SHAP geospatial artificial intelligence (GeoAI) framework for the quantitative analysis of intangible cultural heritage (ICH) soundscapes, using the concept of 'soundscape genes' as the core analytical unit. It integrates geospatial science with machine learning to extract knowledge from complex spatial big data and simulate human perception. The process involves comprehensive data collection (folk songs, 17 geographical factors), digital preprocessing using ArcGIS for standardization, GeoDetector for pre-analysis to quantify factor explanatory power and interactions, CatBoost for establishing nonlinear mapping relationships and generating spatial distribution maps, and SHAP for interpreting nonlinear driving effects and intrinsic linkages. This framework provides an explainable analytical tool for understanding ICH soundscapes as 'the auditory expression of spatial cultural ecosystems'.
The GeoAI framework successfully generated high-precision spatial distribution maps of folk song ICH soundscapes in Jilin Province, predicting distinct patterns for work songs, mountain songs, and lyric folk songs. Work songs dominate, accounting for 56.24% of the predicted soundscape area, primarily in central plateau plains and mountainous regions around Dahei Mountain. Mountain songs constitute 10.44% of the predicted area, prevalent in low mountainous and hilly areas. Lyric folk songs cover 31.34% of the predicted area, concentrated in the Songyuan Plain. Mean annual precipitation, ethnic groups, landform types, GDP, and distance to ancient villages emerged as the five dominant drivers. Significant synergistic effects between natural and cultural factors were identified, with landform type and mean annual precipitation showing the strongest interaction (0.297).
The GeoAI-driven framework offers a robust methodological tool for analyzing the complex coupling between cultural heritage and the geographical environment. It provides scientific support for Jilin Province's ICH protection policies, advocating for 'differentiated spatial management' through 'scientific protection red lines and development buffer zones'. For example, work songs in areas with annual rainfall exceeding 700 mm can be managed through ecological-cultural corridors integrating water heritage, agriculture, and song transmission. Mountain songs in low rainfall, isolated areas (<680 mm rainfall, >150 km from villages) require restricted development intensity to preserve authenticity. Lyric folk songs thrive around sociocultural nodes (within 25 km of cultural protection units) but are negatively impacted between 25-55 km, necessitating protection for traditional gathering spaces. The framework can evolve into an intelligent monitoring and evaluation system for soundscape sustainability, facilitating dynamic adaptation of conservation strategies.
This study successfully applies an integrated GeoAI technology framework to quantify the formation mechanisms and spatial patterns of ICH soundscapes in Jilin Province, providing robust scientific data for musicology and anthropology. It advances local ICH protection models from 'static preservation' to 'dynamic adaptation' by identifying precise geographic and socio-cultural thresholds. The methodological insights contribute to the United Nations 2030 Sustainable Development Goal (SDG 11.4) by providing innovative technologies for cultural heritage protection. Future work will involve integrating multi-source data, developing dynamic soundscape gene databases with enhanced spatiotemporal resolution, and extending the framework to other types of cultural heritage and diverse cultural forms.
700 mm
Critical Precipitation Threshold for Work Songs
680 mm
Precipitation Threshold for Mountain Song Isolation
25 km
Positive Association Radius for Lyric Folk Songs
Enterprise Process Flow
Data Collection (Folk Songs & Factors)
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Data Preprocessing & Standardization
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GeoDetector (Factor Screening & Interaction Validation)
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CatBoost Multi-classification Model (Spatial Prediction)
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SHAP Interpretability Analysis (Driving Mechanisms)
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Research Result (Zoning Maps & Intrinsic Relationships)
| Factor | Work Songs | Mountain Songs | Lyric Folk Songs |
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| Mean Annual Precipitation |
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| Ethnic Groups |
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| Landform Types |
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| Distance to Ancient Villages |
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| Cultural Preservation Units |
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Work Songs & Hydraulic Agricultural Systems
Description: Work songs in Jilin Province, particularly 'haozi,' are intrinsically linked to traditional agricultural practices and water resource management, often found in regions with significant annual precipitation and intensive farming.
Challenge: The modernization of agriculture and changes in traditional labor methods threaten the contexts for 'labor soundscapes,' risking the loss of associated cultural expressions and transmission pathways.
Solution: Establish integrated ecological-cultural corridors that combine water facility maintenance, traditional farming demonstrations, and folk song performances around traditional villages, especially in areas with >700 mm rainfall.
Outcome: Reinforces the 'labor soundscape' as a living heritage, ensuring the continuity of work songs by embedding them within sustainable agricultural and cultural practices, and promoting community-driven transmission.
Mountain Songs & Cultural-Ecological Isolation
Description: Mountain songs, or 'shange,' thrive in the hilly and mountainous regions, maintaining their distinctive high-pitched and elongated tonal characteristics due to relative isolation and specific ecological boundaries (e.g., <680 mm rainfall).
Challenge: External pressures, including uncontrolled tourism development and modern cultural homogenization, can erode the unique authenticity and stylistic features of these regionally specific soundscapes.
Solution: Implement differentiated spatial management with development restrictions within a 150 km radius of ancient villages in relevant cultural-ecological buffer zones, fostering community-endorsed inheritors.
Outcome: Preserves the originality and distinctiveness of mountain songs by protecting their cultural-ecological isolation, preventing performative distortions, and ensuring intergenerational transmission within local communities.
Lyric Folk Songs & Sociocultural Node Preservation
Description: Lyric folk songs, or 'xiaodiao,' are strongly shaped by human cultural reconstruction and historical reinforcement, primarily circulating around sociocultural nodes in multi-ethnic settlements, reflecting complex social interactions.
Challenge: The vitality and transmission of lyric folk songs are vulnerable to the decline of traditional gathering spaces and the weakening of community-driven cultural activities, especially in zones with negative external influences.
Solution: Prioritize protection of sociocultural nodes within 25 km of cultural preservation units and ancient villages, while implementing development restrictions in zones negatively associated (25-55 km) with lyric folk songs. Support inheritors and moderate innovation.
Outcome: Sustains the living transmission of lyric folk songs by safeguarding their key sociocultural hubs, reinforcing their adaptive expression of social interaction, and enabling dynamic cultural development within defined thresholds.
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Implementation Roadmap
A typical timeline for integrating advanced GeoAI solutions into your enterprise.
Phase 01: Discovery & Strategy
Initial consultations to understand your specific cultural heritage assets, existing data infrastructure, and strategic objectives. Data feasibility analysis and custom model design.
Phase 02: Data Integration & Preprocessing
Collection, standardization, and integration of diverse geospatial and cultural heritage datasets. Application of GeoDetector for initial factor validation and interaction analysis.
Phase 03: Model Development & Training
Development and training of the CatBoost classification model using your processed data. Iterative optimization and validation to ensure high accuracy and generalization ability.
Phase 04: Interpretability & Deployment
Application of SHAP for model interpretability, revealing complex driving mechanisms. Deployment of the GeoAI framework and integration with your existing GIS for dynamic monitoring.
Phase 05: Monitoring & Adaptive Management
Continuous monitoring of ICH soundscape patterns and driving factors. Ongoing model refinement and strategic adjustments based on real-world feedback and cultural sustainability goals.
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