Exploration of a Rural Street Environment: The Difference in Sight between Villagers and Tourists
1. Introduction
1.1. The Richness of Research Objects
1.2. Diversification of Research Content
1.3. Realization of Experimental Environment
2. Materials and Methods
2.1. Materials
2.2. Stimulus Selection
2.3. Procedure
3. Analysis
3.1. Analysis of Fixation Duration
A t-test analysis was performed on the data with a mid-length fixation duration (150–900 ms) that were extracted by villagers and tourists in the overall scene and the segmented scene. Because the data distribution did not conform to the normal distribution, nonparametric rank-sum test analysis was used to analyze the cognition of villagers and tourists. At the same time, the step-frequency and saccade data of villagers and tourists were counted.
3.2. Analysis of Road Design Elements
In order to explore which street elements caused the difference, we randomly selected five nodes in each participant’s experiment. According to their eye-movement heat map and gaze trajectory, we counted the elements of concern regarding eye movement in a total of 40 nodes of eight participants, including greening, building facades, doors and windows, low walls, sky, ground, and seven other elements. Through semantic segmentation, the correlations between seven types of road elements and fixation duration data were analyzed.
Factor statistical analysis was conducted as follows: Using the I-VT algorithm supported by aSeeStudio 0.3.35.3 software, the unclassified data were filtered out from the collected data to obtain the correct fixation point. The distribution of the subjects’ fixation points was observed by visual eye-movement heat maps and fixation trajectory maps.
3.3. Dynamic Analysis of Visual Behavior Spaces
In the formula, represents the line-of-sight magnetism of the left visual surface; represents the maximum fixation duration (ms) of the left visual surface;
represents the total stay time of the left visual surface (ms); denotes the number of fixations in the left view;
denotes the total number of fixations in the current three views. Among them, the value range of is 0~100%, and the larger the value, the higher the attraction of the current view.
4. Results
4.1. Statistical Results of Eye-Movement Characteristic Values
4.2. Semantic Segmentation Results of Street Elements
Both villagers and tourists showed attention to greening. The correlation between the experimental data and the view rate of greenery was significantly negatively correlated with the ratio of ground elements, reflecting the difference between people’s instinctive viewing and intentional attention. Although the frequency and visual ratio of greening and ground elements in the field of vision were very high, the fixation point stayed longer on greening than on the ground. In the street, such analysis methods can be used to capture effective environmental elements for design improvement.
4.3. Results of Street Interface Differences
In the closed interface, the villager group paid more attention to the right side of the face than the tourist group. According to their turning behavior and gaze hotspot maps, it was found that the attraction source was the green plants in the flower bed. The tourist group paid more attention to the style of the residential gate on the left side of the view; however, on the whole, the green plants on the right side of the flower bed were close in attractiveness to the two groups of subjects. The reason for the difference between the two groups is that the residential gate had greater attractiveness to the visitors.
In the semi-closed interface, the villager group paid more attention to the enclosed side; the tourist group paid more attention to the side of the natural forest land and had the behaviors of active approaching and continuous turning. On the whole, the attraction of the right wall enclosure to the two groups of subjects was similar. The reason for the difference was that the natural forest land and the continuous enclosure of the characteristic low wall attracted more tourists’ attention.
The combination of street interfaces had different effects on the sight of villagers and tourists. In the closed interface, tourists paid more attention to the artificially constructed and characteristic elements. In the semi-open interface, the villagers did not pay more attention to the natural forest land because of the influence of the greening elements, but they paid more attention to the interface on the side of the street; in the open interface, both villagers and tourists had more visual exploration behavior on natural forest land and were affected by the forms of the space enclosure and greening elements. It can be seen that visual attraction is not only affected by the types of elements, but also by the combination of street interfaces.
4.4. Interview: Memories (Impressions) of the Street
The villagers mostly talked about the three scenes of the educated youth compound, the old supply and marketing cooperatives, and the old village site, and they talked about keywords such as ‘unique’ and ‘first’. According to the information of the village committee, the educated youth compound is the only preserved building of the educated youth in the whole township, which is well preserved and still has considerable landscape value. The old supply and marketing cooperative was the first supply and marketing cooperative in the whole township, and it was also the last supply and marketing cooperative closed in the whole township. In the past, it supported the life and living of the whole village for a long time. The special features of the old village site are that the area is complete, the historical features are still preserved, the green environment is beautiful, and it is the residence of the first batch of settlers since the Ming Dynasty, which has special significance. In addition to the above three scenes, tourists paid more attention to the various styles of brick walls along the way. When the low wall constantly accompanied the path in the human field of vision and could be well combined with the green environment, in the view of tourists, the ‘low wall’ became a representative symbol that was actively close to the observation and touch.
The results show that when the environment is related to group memory, it can easily produce more emotional value. When the appropriate street elements (low walls) appear repeatedly, it deepens people’s memory and helps to shape the impression of the street.
5. Discussion
This study used real-world eye-tracking technology to analyze the cognitive differences between villagers and tourists, two different social groups, in a rural street environment. At the same time, semantic segmentation and dynamic AOI analysis were used to provide an effective means for quantitative research on spatial perception. In addition, in-depth interviews helped us understand the cognitive differences between the two groups. The conclusions of this study mainly include the following points:
-
Reasonable use of green elements for combination design is important. In natural villages, the attractiveness of green environmental factors to the line of sight has a significant advantage. The crowd will unconsciously pay more attention to the green environment without purposeful scanning. However, high-density greening environments are not as attractive as the greening that occurs in the built environment, and the perception (150–900 ms of gazing) often comes from the longer position of the line of sight. The above experimental analysis reflects that a single instance of natural greening or a single building change cannot better influence people’s eye-turning behavior. Even in the case of an interface with high visibility of greenery, the building side with spatial changes and decorative greening can also show a higher intensity of attraction to attention. For example, compared with the fully open greening environment of interface 3, in interface 2, the old buildings in the left-view jungle and the green flower beds in the right-view continuous wall were more attractive visual stimuli.
-
In the design of streets, we should not only pay attention to the use and renewal of single elements, but also pay attention to the use of rhyme and rhythm. The combination design of ‘low wall’ and ‘green plant’, with its high frequency, can easily form an iconic impression, thus forming an impression of the street. In the dynamic analysis of tourists’ sight behavior, it was found that ‘low wall’ and ‘green plant’ attracted their attention to stay at a higher frequency, and it was found in the interview that it formed the tourists’ impressions of the street. In the village-renovation activities of the village in the past three years, the way and shape of the low-wall masonry have been enriched, and a unique symbol of the street has been formed. In the design of environmental improvements, such a combination of identifiable environmental elements can be used to repeatedly appear, form clues and rhythms, and strengthen the formation of this impression. In the village renovation of other villages, we should also pay attention to the spatial impression brought by the combination of elements and improve the quality of the street environment.
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In the in-depth interviews, the indigenous villagers had highly similar collective memories, and these collective memories existed in specific street scenes. In the design of village street environments, we should pay attention to excavating collective memory, protecting spiritual places, reshaping the landscapes of characteristic streets in the village, awakening people’s emotional cognition of street, and promoting the formation of street attraction. In addition, compared with the single interface in the first half of the whole path, ever-changing spatial combinations in village streets can attract people’s attention and arouse people’s expectations for exploration. Therefore, in the design of village streets, we should pay attention to the use of spatial nodes to create a sense of change in the interface and even design ups and downs, with paving and a climax.
The limitations of the study are as follows: Due to the limitations of the research objective and the site, although the differences of different social groups were taken into account, the number of subjects was small due to the physiological limitations of the subjects and the complexity of the experimental conditions, so it needs to be studied with a larger sample size. Secondly, in addition to the macro-differences, such as the street interface in the selected rural street scene, there were also complexities, such as the combination of other elements of the interface. This study explores the influence of green-view interfaces and wall interfaces on line-of-sight attraction, but it does not involve more diverse street elements and their combinations. Thirdly, the experiment adopts a real scene type, and the stimulation environment chosen was a real street environment. Although it highly restores people’s feelings of being in the street, it is also susceptible to accidental factors such as pedestrians and vehicles. Each participant’s line-of-sight data contained complex behavioral factors and a large amount of data. Therefore, it is necessary to study the causes of the subjects’ line-of-sight behavior in a shorter timeline and a more detailed space. This also makes the analysis more and more complex and more susceptible to individual differences. Fourthly, this study has initially found that the villagers’ local memory and the first impression of tourists are the reasons for their deeper cognitive differences. How to use design techniques to establish local memory as a unique symbol of the countryside will also become research content of the next stage.
This study focuses on exploring the feasibility of the experimental method of exploring rural streets in a real way. At the same time, it pays attention to the differences in sight of the different social groups of indigenous villagers and foreign tourists in a rural street environment and obtains design points to improve the rural street environment from the differences. It is important to build a rural street environment that enables villagers to have a sense of belonging and attracts more tourists. The results of this study can provide new ideas for rural street research, contribute to the field of rural design, and help designers better and more clearly understand people’s perception of landscape elements to guide street design. In the future, the sample data will be expanded for more in-depth research, such as exploring the differences in people’s feelings that are caused by spatial combination changes and gradually combining the research into comprehensive spatial research results.
Author Contributions
Conceptualization, H.R. and J.Z.; methodology, L.Z.; software, L.Z.; validation, H.R., J.Z. and L.Z.; formal analysis, L.Z.; investigation, H.R.; resources, H.R.; data curation, J.Z.; writing—original draft preparation, L.Z.; writing—review and editing, H.R.; visualization, L.Z. and X.W.; supervision, J.Z.; project administration, H.R.; funding acquisition, H.R. and Q.W. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by Hebei Provincial Social Science Fund: Research on the Risk Assessment System of National Spatial Planning Based on Sudden Public Health Incidents, Project Approval Number: HB20GL055.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Bioethics Committee of Hebei Engineering University School of Medicine (protocol code: BER-YXY-2023031, approved 10 June 2023).
Informed Consent Statement
Written informed consent has been obtained from the patient(s) to publish this paper.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Conflicts of Interest
Qingqin Wang was employed by the company China Academy of Building Research Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Figure 1.
(a) real-life eye tracker, (b) visual heat maps, (c) annotated trajectory maps, (d) dynamic AOI analysis of gaze-activity data in the subjects’ experiments.
Figure 1.
(a) real-life eye tracker, (b) visual heat maps, (c) annotated trajectory maps, (d) dynamic AOI analysis of gaze-activity data in the subjects’ experiments.
Figure 2.
Test roadmap.
Figure 3.
Photos of subjects’ on-site test.
Figure 3.
Photos of subjects’ on-site test.
Figure 4.
Analysis method.
Figure 4.
Analysis method.
Figure 5.
Custom (dynamic) AOI.
Figure 5.
Custom (dynamic) AOI.
Figure 6.
Three types of street interfaces and their locations.
Figure 6.
Three types of street interfaces and their locations.
Figure 7.
Significant difference in the t-test results of the villagers and the tourists in the overall scene. (*** p ≤ 0.001).
Figure 7.
Significant difference in the t-test results of the villagers and the tourists in the overall scene. (*** p ≤ 0.001).
Figure 8.
The t-test results of villagers and tourists in scenes 1, 2, and 3 were significantly different. (*** p ≤ 0.001).
Figure 8.
The t-test results of villagers and tourists in scenes 1, 2, and 3 were significantly different. (*** p ≤ 0.001).
Figure 9.
The t-test results of villagers and tourists in scenes 4–7 were significantly different. (*** p ≤ 0.001).
Figure 9.
The t-test results of villagers and tourists in scenes 4–7 were significantly different. (*** p ≤ 0.001).
Figure 10.
Correlation analysis of fixation duration with greenery (p = 0.71116) and ground (p = −0.5658).
Figure 10.
Correlation analysis of fixation duration with greenery (p = 0.71116) and ground (p = −0.5658).
Figure 11.
AOI dynamic analysis (a) and line-of-sight heat map (b) and trajectory map (c).
Figure 11.
AOI dynamic analysis (a) and line-of-sight heat map (b) and trajectory map (c).
Table 1.
Examples of artificial semantic segmentation.
Table 1.
Examples of artificial semantic segmentation.
Pixel Statistics | Y1–4 | The Proportion of Elements in the Vision (FP) | |
---|---|---|---|
Greenery: | 17.23% | ||
The sky: | 12.69% | ||
Ground: | 50.16% | ||
Doors and windows: | 3.66% | ||
Wall: | 38.56% | ||
Low wall: | 5.16% | ||
Other: | 0.00% |
Table 2.
Step-frequency statistics of villagers and tourists (m/s).
Table 2.
Step-frequency statistics of villagers and tourists (m/s).
Villager | 1.311 | 1.339 | 1.324 | 1.393 | Mean: | 1.342 |
Tourist | 1.108 | 1.317 | 1.220 | 1.261 | 1.226 |
Table 3.
Statistics of road design elements of concern by eye movement.
Table 3.
Statistics of road design elements of concern by eye movement.
Experimenter Number | Sampling Point Number | Element Statistics | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | Villager (C) | Tourist (Y) | Sum | Miss Distance | |||
C1 | △ | ▽I | △U | △U | ○▽ | ||||||
C2 | △U | △ | △ | U | △ | Greenery: | △ | 70% | 60% | 65% | 10% |
C3 | △ | ☆ | U | △ | △U | The sky: | ○ | 5% | 50% | 52.5% | −45% |
C4 | U | △ | △ | △ | △ | Ground: | □ | 0% | 5% | 2.5% | −5% |
Y1 | ○ | △ | △ | ○ | △ | Doors and windows: | ☆ | 5% | 10% | 7.5% | −5% |
Y2 | U | ○ | △ | △○☆ | △ | Wall: | ▽ | 10% | 5% | 7.5% | 5% |
Y3 | ○☆ | △▽ | △ | △ | △○ | Low wall: | U | 35% | 5% | 20% | 30% |
Y4 | ○ | △○□ | ○ | △ | ○ | Other: | I | 5% | 0% | 2.5% | 5% |
Table 4.
The correlation statistics of fixation duration and elements.
Table 4.
The correlation statistics of fixation duration and elements.
Villager (C) | Tourist (Y) | Whole Correlation | |
---|---|---|---|
Greenery: | 0.70261 | 0.69332 | 0.71116 |
The sky: | 0.13331 | −0.12607 | −0.01706 |
Ground: | −0.60348 | −0.61431 | −0.5658 |
Doors and windows: | −0.38751 | 0.22314 | 0.02776 |
Wall: | 0.17444 | 0.0165 | 0.1025 |
Low wall: | 0.03511 | 0.16728 | 0.08314 |
Other: | −0.27099 | −0.18219 | −0.18768 |
Table 5.
AOI dynamic analysis data and gaze-attraction statistics.
Table 5.
AOI dynamic analysis data and gaze-attraction statistics.
Enclosed Interface | Semi-Enclosed Interface | Open Surface | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Left Visual Surface | Ground | Right Visual Surface | Left Visual Surface | Ground | Right Visual Surface | Left Visual Surface | Ground | Right Visual Surface | |||
Villager (C) | 1 | G | 0.059139785 | 0.023809524 | 0.064327485 | 0.045751634 | 0.027149321 | 0.057189542 | 0.054422317 | 0.029434851 | 0.060932845 |
X | 15 | 5 | 10 | 21 | 9 | 21 | 27 | 3 | 26 | ||
Y | 18.6 | 2.8 | 5.7 | 15.3 | 2.6 | 10.8 | 12.403 | 0.546 | 20.573 | ||
Z | 2.2 | 0.4 | 1.1 | 1.7 | 0.4 | 1.5 | 1.4 | 0.3 | 2.7 | ||
2 | G | 0.037037037 | 0.103174603 | 0.378405651 | 0.125 | 0.225154053 | 0.29342723 | 0.058405469 | 0.076815029 | 0.071092345 | |
X | 1 | 4 | 5 | 1 | 4 | 3 | 5 | 17 | 12 | ||
Y | 0.1 | 5.6 | 21.802 | 4.3 | 37.974 | 1.917 | 4.784 | 22.782 | 10.922 | ||
Z | 0.1 | 3.9 | 16.5 | 4.3 | 17.1 | 1.5 | 1.9 | 3.5 | 2.2 | ||
3 | G | 0.08656558 | 0.077084022 | 0.118128507 | 0 | 0.431992101 | 0.125456204 | 0.037369984 | 0.078313896 | 0.125031447 | |
X | 6 | 12 | 9 | 0 | 7 | 1 | 2 | 22 | 25 | ||
Y | 15.916 | 4.036 | 7.901 | 0 | 8.102 | 14.248 | 0.983 | 22.359 | 26.932 | ||
Z | 6.2 | 0.7 | 2.8 | 0 | 4 | 14.3 | 0.9 | 3.9 | 6.6 | ||
4 | G | 0 | 0.21418756 | 0.169718977 | 0 | 0.102755581 | 0.017857143 | 0.057957015 | 0.06853746 | 0 | |
X | 0 | 13 | 3 | 0 | 55 | 1 | 12 | 28 | 1 | ||
Y | 0 | 17.829 | 9.501 | 0 | 39.188 | 0.134 | 10.1 | 27.9 | 1.3 | ||
Z | 0 | 4.7 | 8.6 | 0 | 4.1 | 0.134 | 2 | 2.8 | 1.3 | ||
Tourist (Y) | 1 | G | 0.070401502 | 0.074517353 | 0.064460607 | 0.0625 | 0.356324765 | 0.023809524 | 0.054996677 | 0.137568293 | 0 |
X | 22 | 19 | 5 | 1 | 14 | 1 | 3 | 32 | 0 | ||
Y | 16.304 | 13.303 | 12.984 | 0.3 | 15.716 | 2.1 | 2.567 | 31.471 | 0 | ||
Z | 2.4 | 2.4 | 7.7 | 0.3 | 6.4 | 0.8 | 1.6 | 4.6 | 0 | ||
2 | G | 0.200711885 | 0.293933709 | 0.076923077 | 0.28584392 | 0.061617458 | 0.117311351 | 0.15154265 | 0.131082423 | 0.125313283 | |
X | 7 | 5 | 1 | 6 | 8 | 5 | 3 | 11 | 5 | ||
Y | 38.9 | 12.3 | 0.3 | 23.2 | 4.1 | 8.3 | 17.4 | 10.6 | 12.6 | ||
Z | 14.5 | 9.4 | 0.3 | 21 | 0.6 | 3.7 | 16.7 | 2.4 | 6 | ||
3 | G | 0.053835204 | 0.026817364 | 0.023314973 | 0.041739782 | 0.039226928 | 0.030449345 | 0.102685624 | 0.055671538 | 0.034425778 | |
X | 40 | 15 | 14 | 21 | 26 | 32 | 17 | 34 | 17 | ||
Y | 18.306 | 8.917 | 3.481 | 8.916 | 11.746 | 9.312 | 3.165 | 14.37 | 3.631 | ||
Z | 1.7 | 1.1 | 0.4 | 1.4 | 1.4 | 0.7 | 1.3 | 1.6 | 0.5 | ||
4 | G | 0.126020768 | 0.188018338 | 0.082365538 | 0.464839094 | 0.142574816 | 0.08583691 | 0.132835244 | 0.061805652 | 0 | |
X | 5 | 9 | 4 | 6 | 3 | 1 | 25 | 2 | 0 | ||
Y | 9.919 | 19.413 | 1.349 | 20.136 | 21.252 | 0.233 | 43.217 | 2.397 | 0 | ||
Z | 4.5 | 7.3 | 0.5 | 15.6 | 10.1 | 0.2 | 6.2 | 2 | 0 |
Table 6.
Comparison of AOI dynamic analysis data.
Table 6.
Comparison of AOI dynamic analysis data.
Villager (C) | Tourist (Y) | |
---|---|---|
Mean: | 0.097 | 0.111 |
Fixation time: | 10.722 | 11.639 |
Residence time: | 11.276 | 11.728 |
Maximum fixation duration: | 3.493 | 4.369 |
Table 7.
The most memorable (impressed) scenes.
Table 7.
The most memorable (impressed) scenes.
Villager (C) | Tourist (Y) | |||||
---|---|---|---|---|---|---|
1 | Educated youth courtyard | Old supply and marketing cooperative | Old village site | Low wall | Yard gate | Low wall |
2 | Educated youth courtyard | Old supply and marketing cooperative | Old village site | Educated Youth courtyard | Shop | Old village site |
3 | Educated youth courtyard | Old supply and marketing cooperative | Old village site | Old supply and marketing cooperative | Low wall | Side of the street |
4 | Bridge | Old supply and marketing cooperative | Old village site | Educated youth courtyard | Old supply and marketing cooperative | Side of the street |
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