{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T19:45:58Z","timestamp":1777405558754,"version":"3.51.4"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T00:00:00Z","timestamp":1770854400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Research Projects for Higher Education Institutions by the Education Department of Liaoning Province","award":["LJ222510153004"],"award-info":[{"award-number":["LJ222510153004"]}]},{"name":"Doctoral Research Startup Project under the 2025 Natural Science Foundation Program of Liaoning Province","award":["2025-BS-0881"],"award-info":[{"award-number":["2025-BS-0881"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Background: Research on spatial imagery as perceived by humans is an important frontier for deepening the theoretical understanding of Tourism Destination Image and promoting sustainable urban development. Significance: This study, from the perspective of tourists, explores the correlation mechanism between the cognitive image and affective image of urban space. This is of great significance for enhancing the overall spatial quality of cities, promoting the integration of the man\u2013land relationship, and driving the sustainable development of tourism. Method: In this study, we took Harbin as the case site, collected 89,375 reviews and 23,561 review images of 488 scenic spots on the Mafengwo and Ctrip platforms, and constructed a multimodal dataset. We classified the image scenes with the help of the Places365-CNN model. We then extracted text emotional features by utilizing the SnowNLP deep learning algorithm. We constructed a map of the spatial influence mechanism acting on cognitive image and emotion through MGWR. Results: The experimental results showed that in the level of Pleasure, the five indicators NHS, HPA, RPA, PDS and WRV had significant spatial correlations with urban sentiment. In the level of Arousal, the three indicators PD, MaSD and WRV showed significant spatial characteristics. Conclusions: This study reveals the influence mechanism of urban spatial perception elements on tourists\u2019 emotions. It not only deepens the understanding of the Tourism Destination Image theory, but also provides a practical path based on the optimization of perception scenarios for the improvement of urban space, which has important implications for regional sustainable development.<\/jats:p>","DOI":"10.3390\/ijgi15020074","type":"journal-article","created":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T15:28:11Z","timestamp":1770910091000},"page":"74","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Mining the Tourism Destination Image and Analyzing Influence Mechanisms"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5778-0128","authenticated-orcid":false,"given":"Shan","family":"Huang","sequence":"first","affiliation":[{"name":"School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3273-4665","authenticated-orcid":false,"given":"Xu","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingqun","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinghua","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"106708","DOI":"10.1016\/j.cities.2025.106708","article-title":"Identifying urban agglomeration\u2019s range: Integrating clustering and accessibility analysis","volume":"171","author":"Zhang","year":"2026","journal-title":"Cities"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103669","DOI":"10.1016\/j.landurbplan.2019.103669","article-title":"Analyzing spatial relationships between urban land use intensity and urban vitality at street block level: A case study of five Chinese megacities","volume":"193","author":"Xia","year":"2020","journal-title":"Landsc. 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