Abstract
Against the backdrop of rapid development in the IST industry, addressing issues such as regional homogeneity and uneven spatiotemporal development requires scientific identification and analysis of related resources to support sustainable regional IST development and promote high-quality regional economic growth. This study proposes a framework based on “policy orientation–theoretical support–regional adaptation,” utilizing machine learning to construct a multi-dimensional evaluation index system for IST development potential. By combining subjective and objective criteria to determine indicator weights, a scientific evaluation system is established, with visual analysis conducted through Geographic Information System (GIS). The research selects 22 indicator factors across four dimensions: natural environmental suitability, socio-economic support capacity, regional transportation accessibility, and tourism appeal. Through weighted superposition analysis, it achieves visual representation of spatial differentiation characteristics in the development potential levels of IST in Heilongjiang Province. Results demonstrate a distinct “V”-shaped distribution of high development potential, primarily concentrated in the Greater Khingan Range region, Harbin–Mudanjiang border zone, and Jiamusi, with gradual decline from the core “V”-shaped area to both sides. The proposed evaluation index system provides scientific quantitative decision-making support for regional IST planning, and this methodology also holds reference value for evaluating other tourism industry developments.
| Original language | English |
|---|---|
| Article number | 337 |
| Journal | Land |
| Volume | 15 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 2026 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- Heilongjiang Province
- IST
- development potential
- evaluation system
- multi-source heterogeneous data
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