{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:17:39Z","timestamp":1760145459734,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,7,18]],"date-time":"2024-07-18T00:00:00Z","timestamp":1721260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2022 Guangdong Province Ordinary University Characteristic Innovation Projects","award":["2022KTSCX135"],"award-info":[{"award-number":["2022KTSCX135"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>With the development of positioning technology and the widespread application of mobile positioning terminal devices, the acquisition of trajectory data has become increasingly convenient. Furthermore, mining information related to scenic spots and tourists from trajectory data has also become increasingly convenient. This study used the normalization results of information entropy to evaluate the attraction of scenic spots and the experience index of tourists. Tourists and scenic spots were chosen as the probability variables to calculate information entropy, and the probability values of each variable were calculated according to certain methods. There is a certain competitive relationship between scenic spots of the same type. When the distance between various scenic spots is relatively close (less than 8 km), a strong cooperative relationship can be established. Scenic spots with various levels of attraction can generally be classified as follows: cultural heritage, natural landscape, and leisure and entertainment. Scenic spots with higher attraction are usually those with a higher A-level and convenient transportation. A considerable number of tourists do not choose to visit crowded scenic destinations but choose some spots that they are more interested in according to personal preferences and based on access to free travel.<\/jats:p>","DOI":"10.3390\/e26070607","type":"journal-article","created":{"date-parts":[[2024,7,18]],"date-time":"2024-07-18T08:39:12Z","timestamp":1721291952000},"page":"607","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluating the Attraction of Scenic Spots Based on Tourism Trajectory Entropy"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6201-8079","authenticated-orcid":false,"given":"Qiuhua","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Geography Information Science, School of Geography and Tourism, Huizhou University, Huizhou 516007, China"}]},{"given":"Linyuan","family":"Xia","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and GIS, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6091-3114","authenticated-orcid":false,"given":"Qianxia","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and GIS, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China"}]},{"given":"Yixiong","family":"Xia","sequence":"additional","affiliation":[{"name":"Foshan Surveying Mapping And Geoinformation Research Institute, Foshan 528000, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/0160-7383(79)90101-4","article-title":"Towards a geography of tourism","volume":"6","author":"Pearce","year":"1979","journal-title":"Ann. 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