2022
DOI: 10.3390/su14073906
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Study of Different Vegetation Types in Green Space Landscape Preference: Comparison of Environmental Perception in Winter and Summer

Abstract: Through field perception in winter and summer, people’s preferences for vegetation types in green spaces with various structures (single-layer woodland, tree-shrub-grass composite woodland, tree-grass composite woodland, and single-layer grassland) and concrete and asphalt sites (areas) without plants are evaluated. The results show the following: (1) There are significant differences in landscape preference between the two seasons, and the environmental perception preference score for landscapes in summer is … Show more

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Cited by 11 publications
(10 citation statements)
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“…According to the path analysis results, sheltered environments, limited spaces, and environments with high species richness may attenuate the psychological repair effect for college students. Cognitive scales of spatial perception, species richness, and sense of shelter influenced people's landscape preferences, consistent with previous findings [47].…”
Section: Campus Green Space Has a Positive Effect On College Students...supporting
confidence: 90%
“…According to the path analysis results, sheltered environments, limited spaces, and environments with high species richness may attenuate the psychological repair effect for college students. Cognitive scales of spatial perception, species richness, and sense of shelter influenced people's landscape preferences, consistent with previous findings [47].…”
Section: Campus Green Space Has a Positive Effect On College Students...supporting
confidence: 90%
“…K-means algorithm belongs to one of the common algorithms in the division method, and its theory also belongs to a basic category of iterative optimization algorithm (optimization clustering), which generally requires the algorithm to satisfy a certain equalization function, as a basic criterion of the basic iterative optimization process, and iterate continuously to get each optimal cluster clusters [22]. Although it is said that the K-means algorithm is relatively easy and fast to implement, in fact, there are some limitations in the process of cluster calculation, iteration, and optimization: (1) the algorithm is sensitive to the initial cluster centroid; (2) it is easy to fall into the local optimal solution [23].…”
Section: K-means Clustering Algorithmmentioning
confidence: 99%
“…. ., 24; first, the whole sample data set is clustered on the A1 dimensional group using the clustering method to obtain three classes of K m,n PSO (1,4,7,10,13,16,19,22), (2, 5, 8, 11, 14, 17 20, 23), and (3,6,9,12,15,18,21,24), and then apply the same method to cluster (1,4,7,10,13,16,19,22) first in A2 dimension to obtain one class (1,4,7,10,13,16,19,22) and cluster (2,5,8,11,14,17,20,23) in A2 dimension to obtain two classes (2,5,8,11,14,17) and (20,23), and one class (3,…”
Section: Empirical Analysismentioning
confidence: 99%
“…People also exhibit preferences for different types of vegetation in green spaces. For instance, compared to tree-shrub-grass composite woodland, individuals prefer single-layer woodland [52].…”
Section: Factors Associated With Spatial Vitalitymentioning
confidence: 99%
“…In future research, exploration and improvement can be undertaken in the following aspects. Regarding indicator selection, consideration could be given to incorporating additional indicators related to plant landscape space characteristics, such as the olfactory features [54], acoustic characteristics [55], and thermal comfort [52]. In terms of method selection, insights from studies on street and urban park spatial vitality can be leveraged to identify other suitable quantifiable vitality indicators.…”
mentioning
confidence: 99%