TY - JOUR

T1 - Research on Landscape Perception of Urban Parks Based on User-Generated Data

AU - Ren, Wei

AU - Zhan, Kaiyuan

AU - Chen, Zhu

AU - Hong, Xin Chen

N1 - Publisher Copyright: © 2024 by the authors.

PY - 2024/9/4

Y1 - 2024/9/4

N2 - User-generated data can reflect various viewpoints and experiences derived from people’s perception outcomes. The perceptual results can be obtained, often by combining subjective public perceptions of the landscape with physiological monitoring data. Accessing people’s perceptions of the landscape through text is a common method. It is hard to fully render nuances, emotions, and complexities depending only on text by superficial emotional tendencies alone. Numerical representations may lead to misleading conclusions and undermine public participation. In addition, the use of physiological test data does not reflect the subjective reasons for the comments made. Therefore, it is essential to deeply parse the text and distinguish between segments with different semantic differences. In this study, we propose a perceptual psychology-based workflow to extract and visualize multifaceted views from user-generated data. The analysis methods of FCN, LDA, and LSTM were incorporated into the workflow. Six areas in Fuzhou City, China, with 12 city parks, were selected as the study object. Firstly, 9987 review data and 1747 pictures with corresponding visitor trajectories were crawled separately on the Dianping and Liangbulu websites. For in-depth analysis of comment texts and making relevant heat maps. Secondly, the process of clauses was added to get a more accurate representation of the sentiment of things based on the LSTM sentiment analysis model. Thirdly, various factors affecting the perception of landscapes were explored. Based on such, the overall people’s perception of urban parks in Fuzhou was finally obtained. The study results show that (1) the texts in terms of ‘wind’, ‘temperature’, ‘structures’, ‘edge space (spatial boundaries)’, and ‘passed space’ are the five most representative factors of the urban parks in Fuzhou; (2) the textual analyses further confirmed the influence of spatial factors on perception in the temporal dimension; and (3) environmental factors influence people’s sense of urban parks concerning specificity, clocking behavior, and comfort feelings. These research results provide indispensable references for optimizing and transforming urban environments using user-generated data.

AB - User-generated data can reflect various viewpoints and experiences derived from people’s perception outcomes. The perceptual results can be obtained, often by combining subjective public perceptions of the landscape with physiological monitoring data. Accessing people’s perceptions of the landscape through text is a common method. It is hard to fully render nuances, emotions, and complexities depending only on text by superficial emotional tendencies alone. Numerical representations may lead to misleading conclusions and undermine public participation. In addition, the use of physiological test data does not reflect the subjective reasons for the comments made. Therefore, it is essential to deeply parse the text and distinguish between segments with different semantic differences. In this study, we propose a perceptual psychology-based workflow to extract and visualize multifaceted views from user-generated data. The analysis methods of FCN, LDA, and LSTM were incorporated into the workflow. Six areas in Fuzhou City, China, with 12 city parks, were selected as the study object. Firstly, 9987 review data and 1747 pictures with corresponding visitor trajectories were crawled separately on the Dianping and Liangbulu websites. For in-depth analysis of comment texts and making relevant heat maps. Secondly, the process of clauses was added to get a more accurate representation of the sentiment of things based on the LSTM sentiment analysis model. Thirdly, various factors affecting the perception of landscapes were explored. Based on such, the overall people’s perception of urban parks in Fuzhou was finally obtained. The study results show that (1) the texts in terms of ‘wind’, ‘temperature’, ‘structures’, ‘edge space (spatial boundaries)’, and ‘passed space’ are the five most representative factors of the urban parks in Fuzhou; (2) the textual analyses further confirmed the influence of spatial factors on perception in the temporal dimension; and (3) environmental factors influence people’s sense of urban parks concerning specificity, clocking behavior, and comfort feelings. These research results provide indispensable references for optimizing and transforming urban environments using user-generated data.

KW - landscape perception

KW - LSTM sentiment analysis

KW - urban parks

KW - user-generated data

UR - http://www.scopus.com/inward/record.url?scp=85205238843&partnerID=8YFLogxK

U2 - 10.3390/buildings14092776

DO - 10.3390/buildings14092776

M3 - Article

AN - SCOPUS:85205238843

VL - 14

JO - Buildings

JF - Buildings

IS - 9

M1 - 2776

ER -