共 56 条
Using Social Media and Multi-Source Geospatial Data for Quantifying and Understanding Visitor's Preferences in Rural Forest Scenes: A Case Study from Nanjing
被引:5
作者:

Wang, Chongxiao
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h-index: 0
机构:
Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China

Zou, Jiahui
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h-index: 0
机构:
Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China

Fang, Xinyuan
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h-index: 0
机构:
Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China

Chen, Shuolei
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h-index: 0
机构:
Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China

Wang, Hao
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h-index: 0
机构:
Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China
机构:
[1] Nanjing Forestry Univ, Sch Landscape Architecture, Nanjing 210037, Peoples R China
来源:
关键词:
rural forest scenes;
visitors' preference;
social media data;
multi-source geospatial data;
Geodetector;
machine learning;
URBAN;
QUALITY;
PARKS;
D O I:
10.3390/f14101932
中图分类号:
S7 [林业];
学科分类号:
0829 ;
0907 ;
摘要:
Rapid urbanization has made urban forest scenes scarce resources, leading to a surge in the demand for high-quality rural forest scenes as alternative outdoor recreation spaces. Previous studies mainly applied survey methods, focusing on visitors' feedback for different types of scenes from the perspective of visual quality evaluation. Nevertheless, the explanations of the relationships between various factors of scenes and visitors' preferences are relatively superficial. This study sought to explore the distribution and characteristics of preferred rural forest scenes based on visitor reviews from social media, and using Geodetector, a geospatial statistics tool, to quantitatively analyzed the reasons for visitors' preferences in terms of factors obtained from multi-source geospatial data. The findings are that (1) visitors are already satisfied with the natural environment but expect scenes that reflect the culture of tea; (2) spatial factor has a more robust interpretation of visitors' preference, and although the Normalized Difference Vegetation Index (NDVI) and non-consumption indicators barely explain visitors' preference solely when each of them is combined with other indicators, they can produce non-linear enhancement effects. Consequently, this study synthesizes visitors' feedback and factors in rural forest scenes to understand visitors' preferences, thus providing insights into human-centered planning.
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