Impact of Landscape Quality of Traditional Village Tourism Destinations on Spatial Vitality： an Empirical Study of Beigang Village in Pingtan County Based on Multi Source Data and Machine Learning

CHEN Zhengyan; LIN Yishan; XIE Jiahui; XIE Zhiqi; XIE Xinqi; DING Zheng

doi:10.3724/j.gyjzG23072603

Volume 55 Issue 9

Sep. 2025

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Article Navigation > INDUSTRIAL CONSTRUCTION > 2025 > 55(9): 104-114

CHEN Zhengyan, LIN Yishan, XIE Jiahui, XIE Zhiqi, XIE Xinqi, DING Zheng. Impact of Landscape Quality of Traditional Village Tourism Destinations on Spatial Vitality： an Empirical Study of Beigang Village in Pingtan County Based on Multi Source Data and Machine Learning[J]. INDUSTRIAL CONSTRUCTION, 2025, 55(9): 104-114. doi: 10.3724/j.gyjzG23072603

Citation:

CHEN Zhengyan, LIN Yishan, XIE Jiahui, XIE Zhiqi, XIE Xinqi, DING Zheng. Impact of Landscape Quality of Traditional Village Tourism Destinations on Spatial Vitality： an Empirical Study of Beigang Village in Pingtan County Based on Multi Source Data and Machine Learning[J]. INDUSTRIAL CONSTRUCTION, 2025, 55(9): 104-114. doi: 10.3724/j.gyjzG23072603

Citation:

CHEN Zhengyan, LIN Yishan, XIE Jiahui, XIE Zhiqi, XIE Xinqi, DING Zheng. Impact of Landscape Quality of Traditional Village Tourism Destinations on Spatial Vitality： an Empirical Study of Beigang Village in Pingtan County Based on Multi Source Data and Machine Learning[J]. INDUSTRIAL CONSTRUCTION, 2025, 55(9): 104-114. doi: 10.3724/j.gyjzG23072603

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Impact of Landscape Quality of Traditional Village Tourism Destinations on Spatial Vitality： an Empirical Study of Beigang Village in Pingtan County Based on Multi Source Data and Machine Learning

doi: 10.3724/j.gyjzG23072603

1. Fujian Agriculture and Forestry University, Fuzhou 350002, China

Received Date: 2023-07-26
Available Online: 2025-11-05

Abstract

Abstract

The vitality of rural tourism destinations is an important factor in the revitalization of traditional village tourism. The widespread application of multi-source data and machine learning analysis systems has broadened the research perspective of rural built-up environments. However， in the current research on the factors affecting rural spatial vitality， there is a lack of more detailed exploration of the causes of human subjective perception factors. This study took Beigang Village， Pingtan County， as the research object. Firstly， the population thermal data， POI （Point of Interest） data， and street scene shooting data were classified and organized. Secondly， the semantic segmentation method and public perception score were used to obtain the proportion and scoring data of landscape elements. Finally， XGBoost （eXtreme Gradient Boosting） method was used to construct the model， and the contribution of different elements was explained through the SHAP （Shapley Additive Explanations） method. The experimental results showed that： 1） Blue vision rate， width， paving degree， and dirtiness are the four most influential indicators， and have a certain non-linear relationship， reflecting the important significance of characteristic landscape construction for enhancing rural spatial vitality. 2） Many indicators， such as green vision rate and blue vision rate， exhibit a distribution pattern of jumping aggregation， indicating weak continuity in landscape planning and design. The conclusion indicates that the fault characterization of different landscape elements and the interaction mechanism between landscape elements and spatial vitality have expanded the application methods of multi-source data and detailed landscape data in meso and micro scale spaces， providing reference for rural tourism destination planning and landscape design.
- traditional village tourism destination,
- spatial vitality,
- landscape quality,
- machine learning,
- multiple source data

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References(25)

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