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To address this, we propose an automated, \u201csurvey\u2010free\u201d analytical paradigm integrating a domain\u2010aligned Large Language Model framework with explainable machine learning. Using Baidu Street View imagery from Xihu (Hangzhou, China), our methodology employs a Vision Encoder and a trainable Connector to map visual features into a fine\u2010tuned Llama3 model, generating multidimensional perception assessments. Validated against expert ground\u2010truth descriptions, these qualitative narratives are seamlessly structured into quantifiable sentiment metrics via a comprehensive Natural Language Processing pipeline. Subsequent explainable modeling uncovers complex, nonlinear threshold dynamics and interactive dependencies between physical visual elements and perception scores. The analysis systematically reveals that the psychological impacts of individual street components are strictly governed by their spatial configurations and structural tipping points. Ultimately, this research demonstrates that combining multimodal AI with explainable algorithms provides a highly scalable and reproducible alternative to traditional surveys. By translating abstract urban observations into precise, data\u2010driven physical design guidelines, this framework empowers urban planners to execute targeted and effective street renewal strategies.<\/jats:p>","DOI":"10.1111\/tgis.70280","type":"journal-article","created":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T05:42:41Z","timestamp":1777959761000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing the Understanding of Urban Street Perception With\n                    <scp>LLM<\/scp>\n                    s and Street View Imagery"],"prefix":"10.1111","volume":"30","author":[{"given":"Xin","family":"Han","sequence":"first","affiliation":[{"name":"School of Landscape Architecture Zhejiang A&amp;F University  Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Architecture Southeast University  Nanjing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7067-3732","authenticated-orcid":false,"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zikun","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering Kyungpook National University  Daegu South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,5,4]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.landurbplan.2024.105131"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1177\/23998083241235495"},{"key":"e_1_2_10_4_1","unstructured":"Devlin J. 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