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Analysis of Forest Landscape Preferences and Emotional Features of Chinese Forest Recreationists Based on Deep Learning of Geotagged Photos

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成果类型:
期刊论文
作者:
Zeng, Xitong;Zhong, Yongde;Yang, Lingfan;Wei, Juan;Tang, Xianglong
通讯作者:
Zhong, Yongde(ade@csuft.edu.cn)
作者机构:
[Zeng, Xitong; Zhong, Yongde; Wei, Juan; Tang, Xianglong] College of Forestry, Central South University of Forestry and Technology, Changsha
410000, China
College of Tourism, Central South University of Forestry and Technology, Changsha
National Forestry and Grassland Administration State Forestry Administration Engineering Research Center for Forest Tourism, Changsha
[Yang, Lingfan] Beijing Zoo, Beijing
通讯机构:
[Yongde Zhong] N
National Forestry and Grassland Administration State Forestry Administration Engineering Research Center for Forest Tourism, Changsha 410000, China<&wdkj&>College of Tourism, Central South University of Forestry and Technology, Changsha 410000, China<&wdkj&>College of Forestry, Central South University of Forestry and Technology, Changsha 410000, China<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
deep learning;deepsentibank;forest landscape;geotagged photos;sentiment analysis
期刊:
Forests
ISSN:
1999-4907
年:
2022
卷:
13
期:
6
页码:
892-
基金类别:
Conceptualization, X.Z.; Data curation, X.Z. and X.T.; Funding acquisition, Y.Z. and L.Y.; Methodology, X.Z.; Project administration, Y.Z.; Supervision, Y.Z. and J.W.; Validation, Y.Z., J.W. and X.T.; Visualization, X.Z. and J.W.; Writing—original draft, X.Z.; Writing—review and editing, Y.Z. and L.Y. All authors have read and agreed to the published version of the manuscript. This research was funded by the Ministry of Science and Technology of The People’s Republic of China, grants 2019YFD1100400. This research was funded by the science and technology innovation Program of Hunan Province: Research and application of expressway landscape and regional culture integration technology based on Huxiang Culture, grant number 2021SK2050. This research was funded by the Central South University of Forestry and Technology, grants CX202102098.
机构署名:
本校为第一且通讯机构
院系归属:
林学院
旅游学院
摘要:
Forest landscape preference studies have an important role and significance for forest landscape conservation, quality improvement and utilization. However, there are few studies on objective forest landscape preferences from the perspective of plants and using photos. This study relies on Deep Learning technology to select six case sites in China and uses geotagged photos of forest landscapes posted by the forest recreationists on the “2BULU” app as research objects. The preferences of eight forest landscape scenes, including look down lands...

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