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Tourist Landscape Preferences in a Historic Block Based on Spatiotemporal Big Data-A Case Study of Fuzhou, China

International journal of environmental research and public health, 2022-12, Vol.20 (1), p.83 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1660-4601 ;ISSN: 1661-7827 ;EISSN: 1660-4601 ;DOI: 10.3390/ijerph20010083 ;PMID: 36612401

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  • Title:
    Tourist Landscape Preferences in a Historic Block Based on Spatiotemporal Big Data-A Case Study of Fuzhou, China
  • Author: Liu, Fan ; Sun, Danmei ; Zhang, Yanqin ; Hong, Shaoping ; Wang, Minhua ; Dong, Jianwen ; Yan, Chen ; Yang, Qin
  • Subjects: Big Data ; China ; Construction ; Cultural heritage ; Heat ; Hot Temperature ; Landscape architecture ; Optimization ; Preferences ; Questionnaires ; Regression analysis ; Research methodology ; Social networks ; Surveys and Questionnaires ; Sustainable Development ; Temporal variations ; Tourism ; Tourists
  • Is Part Of: International journal of environmental research and public health, 2022-12, Vol.20 (1), p.83
  • Description: Historic blocks are valuable architectural and landscape heritage, and it is important to explore the distribution characteristics of tourists to historic blocks and their landscape preferences to realize the scientific construction and conservation of historic blocks and promote their sustainable development. At present, few studies combine the analysis of tourist distribution characteristics with landscape preferences. This study takes the historic block of Three Lanes and Seven Alleys in Fuzhou as an example, combines field research and questionnaires to construct a landscape preference evaluation indicator system for the historic block, measures the distribution characteristics of tourists in the block through the heat value of tourist flow obtained from the Tencent regional heat map, and analyses the influence of landscape preference indicators on the heat value of tourist flow in the block through stepwise multiple linear regression. The research shows that: (1) the spatial and temporal variation in the heat value of tourist flow tends to be consistent throughout the block, from 7 a.m. to 6 p.m., showing a "rising, slightly fluctuating and then stabilizing" state, both on weekdays and on weekends. (2) The factors influencing the heat value of tourist flow in the different spatial samples are various, with commercial atmosphere, plant landscape, accessibility of the road space, architecture, and the surrounding environment having a significant impact on the heat value of tourist flow. Based on the analysis of the landscape preferences of tourists in the historic block, a landscape optimization strategy is proposed to provide a reference for the management and construction of the block.
  • Publisher: Switzerland: MDPI AG
  • Language: English
  • Identifier: ISSN: 1660-4601
    ISSN: 1661-7827
    EISSN: 1660-4601
    DOI: 10.3390/ijerph20010083
    PMID: 36612401
  • Source: Geneva Foundation Free Medical Journals at publisher websites
    MEDLINE
    PubMed Central
    ProQuest Central
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