Resident Effect Perception in Urban Spaces to Inform Urban Design Strategies
Abstract
:1. Introduction
1.1. Transformation of Urban Design towards Resident Emotion Orientation
1.2. Perspectives Brought by the Emergence of Deep Learning-Based Intelligent Technologies
1.3. Problem Statement and the Overall Methodological Framework
- (1)
- To construct a multi-dimensional research system of 10 m × 10 m small-scale spatial units through combining field research and artificial intelligence analysis methods;
- (2)
- To examine emotional effects of space on age segmentation and gender segmentation based on analyzing data;
- (3)
- To evaluate the emotional effects of design solutions on specific groups of people based on the pattern of effects.
2. Methodology
2.1. Experimental Design
2.2. Participants
2.3. Experiment Site and Equipment
2.4. Procedure
2.5. Measures
2.5.1. Spaces Recognition
2.5.2. Identification of Element Type, Proportion, and Distribution of Flat Urban Space Design Planes
2.5.3. Emotion Recognition of the Population
2.5.4. Number Recognition of the Population
2.5.5. Age and Gender Recognition of the Population
2.6. Statistical Analysis
3. Results
3.1. Emotional Effects of the Spaces on the Participants
3.2. Total Effects and Emotional Effects of the Spaces on People of Different Ages
3.3. Effects of the Spaces on People of Different Genders
4. Discussion
4.1. Evaluation of the Current Space and the Design of the Post-Design Space
4.2. Limitations
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Type of Elements | Proportion of Each Element | Distribution Position of Each Element | Distribution Shape of Each Element |
---|---|---|---|
Water | 8% | South side | Faceted |
Grassland | 6% | North side | Ribbon |
Woods | 3% | South side | Point-like |
Structures | 9% | North side (surrounded by grass) | Ribbon |
Seats | 2% | South side (surrounding water body) | Ribbon |
Wooden pavement | 72% | Central side | Faceted |
Type of Elements | Proportion of Each Element | Distribution Position of Each Element | Distribution Shape of Each Element |
---|---|---|---|
Woods | 2% | South side | Point-like |
Wooden pavement | 98% | Central side | Faceted |
Type of Elements | Proportion of Each Element | Distribution Position of Each Element | Distribution Shape of Each Element |
---|---|---|---|
Water | 9% | South side | Faceted |
Grassland | 14% | North side | Ribbon |
Woods | 4% | South side | Point-like |
Structures | 5% | North side (surrounded by grass) | Ribbon |
Seats | 2% | South side (surrounding water body) | Ribbon |
Wooden pavement | 66% | Central side | Faceted |
Type of Elements | Proportion of Each Element | Distribution Position of Each Element | Distribution Shape of Each Element |
---|---|---|---|
Stone/concrete pavement | 2% | East side | Ribbon |
Water | 9% | South side | Faceted |
Grassland | 13% | North side | Ribbon |
Woods | 4% | South side | Point-like |
Structures | 14% | North side (surrounded by grass) | Ribbon |
Seats | 2% | South side (surrounding water body) | Ribbon |
Landscape lighting | 1% | Northwest side | Point-like |
Wooden pavement | 55% | Central side | Faceted |
Type of Elements | Proportion of Each Element | Distribution Position of Each Element | Distribution Shape of Each Element |
---|---|---|---|
Stone/concrete pavement | 11% | Central side | Ribbon |
Water | 7% | South side | Faceted |
Grassland | 8% | North side | Ribbon |
Woods | 2% | South side | Point-like |
Structures | 8% | North side (surrounded by grass) | Ribbon |
Seats | 2% | South side (surrounding water body) | Ribbon |
Landscape lighting | 3% | Northwest side | Point-like |
Wooden pavement | 59% | Central side | Faceted |
Spatial Elements | Expect | Before | Difference | Expect | After | Difference |
---|---|---|---|---|---|---|
Sky | 0.000 | 0.200 | 0.200 | 0.000 | 0.253 | 0.253 |
Landscape Structures | 0.013 | 0.000 | −0.013 | 0.013 | 0.107 | 0.093 |
House | 0.184 | 0.215 | 0.030 | 0.184 | 0.173 | −0.011 |
Trees | 0.196 | 0.063 | −0.133 | 0.196 | 0.240 | 0.044 |
Grassland | 0.000 | 0.307 | 0.307 | 0.000 | 0.147 | 0.147 |
Road | 0.061 | 0.215 | 0.154 | 0.061 | 0.053 | −0.008 |
Water | 0.162 | 0.000 | −0.162 | 0.162 | 0.000 | −0.162 |
Seats | 0.104 | 0.000 | −0.104 | 0.104 | 0.000 | −0.104 |
Pavilion | 0.104 | 0.000 | −0.104 | 0.104 | 0.000 | −0.104 |
Vessels | 0.053 | 0.000 | −0.053 | 0.053 | 0.000 | −0.053 |
Bridge | 0.047 | 0.000 | −0.047 | 0.047 | 0.027 | −0.021 |
Kids | 0.041 | 0.000 | −0.041 | 0.041 | 0.000 | −0.041 |
Plaza | 0.018 | 0.000 | −0.018 | 0.018 | 0.000 | −0.018 |
Animals | 0.015 | 0.000 | −0.015 | 0.015 | 0.000 | −0.015 |
p value | 0.255 | p value | 0.441 | |||
SD value | 0.129 | SD value | 0.103 |
Spatial Elements | Expect | Before | Difference | Expect | After | Difference |
---|---|---|---|---|---|---|
Sky | 0.225 | 0.324 | 0.099 | 0.225 | 0.303 | 0.078 |
Mountains | 0.000 | 0.261 | 0.261 | 0.000 | 0.000 | 0.000 |
Trees | 0.109 | 0.052 | −0.057 | 0.109 | 0.099 | −0.010 |
Water | 0.205 | 0.363 | 0.158 | 0.205 | 0.158 | −0.047 |
Cloud | 0.000 | 0.000 | 0.000 | 0.000 | 0.092 | 0.092 |
Structures | 0.122 | 0.000 | −0.122 | 0.122 | 0.086 | −0.037 |
House | 0.102 | 0.000 | −0.102 | 0.102 | 0.158 | 0.055 |
Seats | 0.058 | 0.000 | −0.058 | 0.058 | 0.000 | −0.058 |
Pavilion | 0.058 | 0.000 | −0.058 | 0.058 | 0.105 | 0.047 |
Vessels | 0.030 | 0.000 | −0.030 | 0.030 | 0.000 | −0.030 |
Bridge | 0.026 | 0.000 | −0.026 | 0.026 | 0.000 | −0.026 |
Kids | 0.023 | 0.000 | −0.023 | 0.023 | 0.000 | −0.023 |
Plaza | 0.021 | 0.000 | −0.021 | 0.021 | 0.000 | −0.021 |
Animals | 0.020 | 0.000 | −0.020 | 0.020 | 0.000 | −0.020 |
p value | 0.255 | p value | 0.427 | |||
SD value | 0.101 | SD value | 0.046 |
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Zhao, Z.; Wu, Z.; Zhou, S.; Dong, W.; Gan, W.; Zou, Y.; Wang, M. Resident Effect Perception in Urban Spaces to Inform Urban Design Strategies. Land 2023, 12, 1908. https://doi.org/10.3390/land12101908
Zhao Z, Wu Z, Zhou S, Dong W, Gan W, Zou Y, Wang M. Resident Effect Perception in Urban Spaces to Inform Urban Design Strategies. Land. 2023; 12(10):1908. https://doi.org/10.3390/land12101908
Chicago/Turabian StyleZhao, Zichen, Zhiqiang Wu, Shiqi Zhou, Wen Dong, Wei Gan, Yixuan Zou, and Mo Wang. 2023. "Resident Effect Perception in Urban Spaces to Inform Urban Design Strategies" Land 12, no. 10: 1908. https://doi.org/10.3390/land12101908