{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124592"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124592","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Botanic garden visitors’ preference analysis - A case study of Chicago botanic garden","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_has_math":false,"creators":["Huang, Hexiang"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.L.A.","degree_level":"Thesis","degree_discipline":"Landscape Architecture","degree_department":null,"school":null,"contributors":["Deal, Brian","Sullivan, William C.","Lemon, Kelley","Fang, Fang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:02Z","subjects":["Landscape Spatial Analysis","Visitor Preferences","User-generated Content"],"languages":["en","eng"],"rights":["Copyright 2024 Hexiang Huang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124592","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Deal, Brian","Sullivan, William C.","Lemon, Kelley","Fang, Fang"]},{"key":"dc:creator","label":"Author","values":["Huang, Hexiang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-05-03"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Landscape Architecture"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.L.A."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Landscape Spatial Analysis","Visitor Preferences","User-generated Content"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Hexiang Huang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124592"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Hexiang Huang, accepted the attached license on 2024-05-01 at 22:51.","The student, Hexiang Huang, submitted this Thesis for approval on 2024-05-01 at 23:14.","This Thesis was approved for publication on 2024-05-03 at 09:29.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20691 on 2024-09-16 at 00:44:51","User-generated content (UGC) offers an extensive and readily accessible data source for understanding visitor preferences and experiences in natural landscapes. However, there is a lack of large-scale spatial analysis of UGC images depicting landscapes. This study introduces a novel framework that systematically manages and analyzes landscape UGC data to investigate visitor preferences at the Chicago Botanic Garden. The methodology involves web scraping Google Maps reviews and photos, employing generative AI models for computer vision-based image analysis, and applying natural language processing techniques for text analysis. Landscape spatial structure types, elements, components, and plant species are systematically categorized and quantified from the images, while sentiment analysis extracts visitors' feedback and experiences from the text reviews. The results provide insights into the most favored landscape spaces, elements, and specific components that enhance visitor experiences. The efficacy of integrating UGC data analysis with GenAI models is demonstrated, bridging existing research gaps concerning spatial assessment and quantification of visitors' landscape preferences. This study contributes methodological advances in utilizing UGC for landscape research and offers practical implications to empower landscape managers and designers in creating visitor-centric spaces aligned with user preferences. The systematic management of landscape UGC data presents a viable complementary approach to conventional visitor survey methods for landscape design and management."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Botanic garden visitors’ preference analysis - A case study of Chicago botanic garden"]}]}],"canonical_facts":{"dc:contributor":["Deal, Brian","Sullivan, William C.","Lemon, Kelley","Fang, Fang"],"dc:creator":["Huang, Hexiang"],"dc:date":["2024-05","2024-05-03"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Hexiang Huang, accepted the attached license on 2024-05-01 at 22:51.","The student, Hexiang Huang, submitted this Thesis for approval on 2024-05-01 at 23:14.","This Thesis was approved for publication on 2024-05-03 at 09:29.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20691 on 2024-09-16 at 00:44:51","User-generated content (UGC) offers an extensive and readily accessible data source for understanding visitor preferences and experiences in natural landscapes. However, there is a lack of large-scale spatial analysis of UGC images depicting landscapes. This study introduces a novel framework that systematically manages and analyzes landscape UGC data to investigate visitor preferences at the Chicago Botanic Garden. The methodology involves web scraping Google Maps reviews and photos, employing generative AI models for computer vision-based image analysis, and applying natural language processing techniques for text analysis. Landscape spatial structure types, elements, components, and plant species are systematically categorized and quantified from the images, while sentiment analysis extracts visitors' feedback and experiences from the text reviews. The results provide insights into the most favored landscape spaces, elements, and specific components that enhance visitor experiences. The efficacy of integrating UGC data analysis with GenAI models is demonstrated, bridging existing research gaps concerning spatial assessment and quantification of visitors' landscape preferences. This study contributes methodological advances in utilizing UGC for landscape research and offers practical implications to empower landscape managers and designers in creating visitor-centric spaces aligned with user preferences. The systematic management of landscape UGC data presents a viable complementary approach to conventional visitor survey methods for landscape design and management."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124592"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Hexiang Huang"],"dc:subject":["Landscape Spatial Analysis","Visitor Preferences","User-generated Content"],"dc:title":["Botanic garden visitors’ preference analysis - A case study of Chicago botanic garden"],"dc:type":["text"],"thesis:degree_discipline":["Landscape Architecture"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.L.A."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}