2026-09-22T00:11:30Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/124592 2026-01-14 col_2142_5131 col_2142_16314 com_2142_5130 com_2142_9450 com_2142_5126

Deal, Brian Sullivan, William C. Lemon, Kelley Fang, Fang 2024-05 application/pdf en text 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 Botanic garden visitors’ preference analysis - A case study of Chicago botanic garden Huang, Hexiang 2024-05-03 Landscape Spatial Analysis Visitor Preferences User-generated Content 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. Text eng https://hdl.handle.net/2142/124592 Copyright 2024 Hexiang Huang M.L.A. Thesis Landscape Architecture University of Illinois at Urbana-Champaign Landscape Architecture