Evaluating Lightscape Perception in Urban Parks: A Fuzzy Comprehensive Approach with Case Study of Shuixi Park, Tianjin

Abstract

The visual perception of lightscapes in urban parks plays a pivotal role in shaping the quality of recreational experiences. Scientifically delineating the key perceptual components and cultivating visually compelling lightscape environments is essential for enhancing public engagement with urban green spaces. However, extant research often lacks a comprehensive identification of lightscape elements, leading to insufficiently targeted and fragmented design strategies. Furthermore, the sociocultural and psychological dimensions of light perception remain underexplored, with limited attention to human–environment interaction. To address this gap, the present study introduces a multi-dimensional lightscape perception evaluation system grounded in fuzzy set theory, encompassing 19 indicators across social, spatial, and experiential domains. Taking Shuixi Park in Tianjin as an empirical case, expert-based weighting and a structured questionnaire (N = 177) were employed to derive a composite satisfaction score of 3.969 (out of 5), with the experiential domain (e.g., light sensitivity, dynamism) achieving the highest score (4.311). The findings inform design strategies aimed at enhancing perceptual and environmental quality in urban parks and provide a theoretical foundation for the systematic integration of perceptual insights into visual landscape planning.

1. Introduction

With the acceleration of urban life, the functional expectations placed upon public recreational spaces have steadily increased. Urban parks, as multifunctional outdoor activity venues open to the public, have naturally become ideal spaces for the expression of both the spiritual and material cultures of the people [1]. For a long time, the focus of landscape design has centered on tangible elements—such as plant species selection, spatial configuration, water features, and paving materials—which have long constituted the foundation of modern garden and urban landscape development [2]. However, ambient components such as lightscapes and soundscapes—derivatives of these physical constructs—have not received equivalent attention, often resulting in homogenous spatial aesthetics and the perpetuation of formulaic landscape impressions [3]. As societal expectations regarding environmental quality evolve, there is a growing emphasis on integrating sensory dimensions such as sound, scent, and particularly light into landscape design [4,5]. The term “soundscape” was introduced in the 1960s by Canadian musicologist R. Murray Schafer [6], followed by “smellscape” in the 1980s by geographer Porteous [7]. In contrast, although light is the primary medium of human visual perception and a vital channel for environmental information—and although light-related technologies and research methods have a long history internationally [8]—the development of lightscape as a unique academic discipline has emerged only in recent years in China [9]. Chinese scholar Wu Shuoxian formally introduced the concept of “lightscape” [10] and advocated for the establishment of “lightscape studies” as a distinct academic discipline [11]. His initiative was subsequently endorsed in a special editorial in the Architectural Journal, signifying a foundational moment in the academic development of this field.

The exploration of lightscape perception elements is a key component of lightscape planning, serving as a fundamental point for summarizing methods for creating and evaluating urban and garden lightscapes. This approach entails in-depth observation of natural landscapes or the extraction of useful elements from the built environment, historical documents, and literary works to inform lightscape creation [12]. This enables landscape planners and decision-makers to identify which elements, how they should be incorporated, and to what extent they influence the effectiveness of lightscape creation. Understanding lightscape creation models in various regions is vital for determining the most effective methods for creation or improvement. For instance, Li Yating and colleagues [13] argue that “moonlight” is a significant element in the creation of nighttime lightscapes, emphasizing that the creation of moonlight scenes is not merely about physical indicators such as brightness and illuminance, but is more aligned with the spiritual perception of “homesickness” [14] in Chinese culture. Other scholars, such as Bian Yu [15], suggest that the sentiment of “homesickness” is a result of the combined effects of environmental and landscape features, and plant landscapes play an irreplaceable role in the creation of lightscapes. Wu Jihong [16] and Wei Yi [17] have provided fresh perspectives on the construction of urban light environments through their analysis of light phenomena in folklore and Chinese poetry. Qiu Jianzhen [18], among others, has explored differences in the creation of glow-in-the-dark lightscapes in China and Japan from the perspective of lightscape studies.

When limited theoretical achievements are applied to guide landscape practice yet still fail to produce satisfactory lightscape outcomes, it becomes imperative to investigate the underlying causes [19]. The obstacles to applying lightscape perception elements in lightscape construction and evaluation can be outlined as follows: First, evaluation systems for lightscape design typically encompass a multitude of indicators. Table 1 reviews existing studies on the composition of lightscape perception elements and their corresponding weight calculation methods. Evidently, these indicators are often highly complex and consist of both social and physical dimensions. This complexity makes it difficult for designers to discern the primary driving forces behind effective lightscape creation, thereby impeding the selection of appropriate design strategies. In other words, the lightscape perception elements do not always align with the evaluation indicators. For example, lightscape perception elements are often physical entities such as plant landscapes, while evaluation indicators tend to focus on physical factors such as brightness and illuminance. This imbalance, which emphasizes metric priority while neglecting the interrelationships among perceptual elements, may result in ineffective lightscape strategies. Second, a limited number of studies have attempted to define perceptual factors through combinations such as “attention mechanisms” and “landscape element combination”, and have further proposed differentiated responses for various spatial zones [20,21]. However, a serious flaw in these studies is that the driving factors remain focused on the creation of virtual landscapes rather than lightscape-specific indicators, resulting in overly general recommendations. For instance, certain regions may employ classical techniques such as “borrowed scenery” in garden design to enhance lightscape effects [22], yet it remains unclear which specific measures should be implemented. Moreover, for differing spatial contexts, there is insufficient clarity on whether identical response strategies should be adopted [19]. In reality, landscape creation is far more nuanced, and only by further clarifying the concrete drivers of lightscape perception can more precise and reliable strategies be developed. Furthermore, we observe that some studies evaluating lightscapes in specific regions rely on single indicators to represent public acceptability. While such approaches may directly identify driving indicators and yield actionable suggestions, they risk overlooking other critical dimensions, including human behavior and environmental interactions. As a result, the accuracy and comprehensiveness of these assessments are questionable, as most studies of this nature adopt multi-indicator systems to ensure a more holistic evaluation. For example, Chen Ranpeng [23] explored key influencing factors for lightscape creation in different zones based on visual comfort; however, the conclusions remained focused on broad regional scales and failed to illuminate differences in driving elements across spatial contexts. These challenges likely explain the considerable gap between recommendations proposed in previous research and their successful application in real-world lightscape design.

Moreover, it is worth noting that there is currently no universally applicable lightscape perception evaluation system on the international stage. As clearly demonstrated in Table 1, significant discrepancies exist in both the structural components and computational methodologies of existing evaluation systems. These inconsistencies hinder the direct transferability of conclusions or response strategies derived from one urban context to another. Therefore, there is an urgent need for a bridging framework that systematically links lightscape perception elements with responsive strategies, thereby enabling cities to formulate appropriate interventions based on lightscape assessment outcomes.

In summary, the identification of perception elements within urban park lightscapes represents a critical first step in the process of lightscape creation, while the evaluation of such perception forms the necessary second step. Previous research has typically approached lightscape perception from the level of rules or guidelines, primarily focusing on tangible elements associated with light and environmental features. However, such approaches often overlook the intricate complexity present at the indicator level, particularly the array of human-centered elements involved in light perception [24]. Addressing this gap, the present study seeks to develop a methodology for identifying the underlying driving indicators of lightscape perception and to construct a comprehensive evaluation framework. This is essential for informing the formulation of planning and restoration policies for park lightscapes. Our emphasis on the lightscape perception evaluation system stems from its role as a vital bridge between assessment outcomes and actionable strategies. An ambiguous or ill-defined evaluation system may mislead decision-makers, ultimately depriving residents of the opportunity to enjoy enhanced recreational experiences shaped by thoughtful lightscape design. Tianjin (39.08° N, 117.19° E), a port city in northern China, is characterized by its historically rich urban parks [25], offering practical significance for the preservation of cultural and historical heritage. Based on extensive field investigations conducted in Shuixi Park, this study identified 19 key perceptual indicators for inclusion in the proposed evaluation system. Using expert scoring to assign relative weights to each indicator, the system was applied to assess urban lightscape perception within the park. Compared with traditional evaluation models, our system introduces—for the first time—the dimension of “human behavioral activity” as a core component. This addition enables a holistic assessment of lightscape quality from the interrelated perspectives of people, light, and environment. Ultimately, this research establishes a novel evaluation system for urban park lightscapes that broadens our understanding of perceptual elements and offers decision-makers a robust framework for determining targeted methods for the creation or enhancement of lightscapes in specific urban areas.

Table 1. A review of research on elements and evaluation indicators of lightscapes perception.

Author and Year	Indicators	Total Variables	Method
Hong Xinchen et al. [26] (2019)	Physical factors: Illumination uniformity; Daylighting coefficient; Brightness ratio; Color temperature Psychological Factors: Lightscape scarification; Audio-Visual coordination; Privacy; Security Spatial factors: Sky view factor; Clear bole height; Stand density; Crown density	12	Analytic Hierarchy Process (AHP)
Qiu Jianzhen et al. [27] (2022)	Quality of emotional perception: Satisfaction; Comfort; Pleasantness; Vitality; Interestingness; Impressiveness Lightscapes characteristic perception: Luminance; Intensity; Luminance uniformity; Mode of illumination; Light color; Color richness; Dynamicity; Rhythmicity; Cultural connotations Ambient spatial atmosphere: Seasonal sense; Aesthetics; Coherence; Orderliness; Naturalness; Tradition Social tendencies: Sociality; Safety	40	Semantic Differences Scale
Qiu Jianzhen et al. [28] (2020) ADDIN	Characteristic lightscapes identity; Differences in lightscapes preferences; Importance of Lightscape; Comfort of the Lightscape; Satisfaction with lightscapes	5	Post Occupancy Evaluation (POE)
Huang Haijing et al. [4] (2024)	Quality of emotional perception: Satisfaction; Comfort; Pleasantness; Vitality; Interestingness; Impressiveness Lightscapes characteristic perception: Luminance; Intensity; Luminance uniformity; Mode of illumination; Light color; Color richness; Dynamicity; Rhythmicity; Cultural connotations Ambient spatial atmosphere: Seasonal sense; Aesthetics; Coherence; Orderliness; Naturalness; Tradition Social tendencies: Sociality; Safety	23	Semantic Differences Scale
Qi Chaohui [29] (2019)	Overall impression: Spaciousness; Sense of order; A sense of hierarchy, Sense of beauty; Sense of color; Seasonality; Pleasure; Seclusion; Richness; Attractiveness; Visual impact; Vegetation diversity Perception of light and shade: Light perception; Projection clarity; Projection coverage; Aesthetics of light and shadow; Sense of mood; Novelty; Vitality; Softness; Dynamism; Harmony; Variety; Functionality	24	Semantic Differences Scale
Chen Ranpeng [23] (2022)	Visual comfort; park beauty; light color richness; ambient quietness; light ambience; light character; spatial experience coherence; nighttime visual luminance; sense of mood; environmental cleanliness; light color tendency; light coordination; history	13	Questionnaires and semi-structured interviews
Wang Yirui [30] (2020)	Physics dimension: Temperature and brightness Aesthetics dimension: The light source itself; Illuminated object; The expression form; Light form; Rhythm; Color Space dimension: Boundary sense; Domain sense; Direction sense Time dimension: Time changes; Seasonal changes Psychology dimension: Style atmosphere; Emotional experience; Cultural association	15	online questionnaire surveys

Table 1. A review of research on elements and evaluation indicators of lightscapes perception.

Author and Year	Indicators	Total Variables	Method
Hong Xinchen et al. [26] (2019)	Physical factors: Illumination uniformity; Daylighting coefficient; Brightness ratio; Color temperature Psychological Factors: Lightscape scarification; Audio-Visual coordination; Privacy; Security Spatial factors: Sky view factor; Clear bole height; Stand density; Crown density	12	Analytic Hierarchy Process (AHP)
Qiu Jianzhen et al. [27] (2022)	Quality of emotional perception: Satisfaction; Comfort; Pleasantness; Vitality; Interestingness; Impressiveness Lightscapes characteristic perception: Luminance; Intensity; Luminance uniformity; Mode of illumination; Light color; Color richness; Dynamicity; Rhythmicity; Cultural connotations Ambient spatial atmosphere: Seasonal sense; Aesthetics; Coherence; Orderliness; Naturalness; Tradition Social tendencies: Sociality; Safety	40	Semantic Differences Scale
Qiu Jianzhen et al. [28] (2020) ADDIN	Characteristic lightscapes identity; Differences in lightscapes preferences; Importance of Lightscape; Comfort of the Lightscape; Satisfaction with lightscapes	5	Post Occupancy Evaluation (POE)
Huang Haijing et al. [4] (2024)	Quality of emotional perception: Satisfaction; Comfort; Pleasantness; Vitality; Interestingness; Impressiveness Lightscapes characteristic perception: Luminance; Intensity; Luminance uniformity; Mode of illumination; Light color; Color richness; Dynamicity; Rhythmicity; Cultural connotations Ambient spatial atmosphere: Seasonal sense; Aesthetics; Coherence; Orderliness; Naturalness; Tradition Social tendencies: Sociality; Safety	23	Semantic Differences Scale
Qi Chaohui [29] (2019)	Overall impression: Spaciousness; Sense of order; A sense of hierarchy, Sense of beauty; Sense of color; Seasonality; Pleasure; Seclusion; Richness; Attractiveness; Visual impact; Vegetation diversity Perception of light and shade: Light perception; Projection clarity; Projection coverage; Aesthetics of light and shadow; Sense of mood; Novelty; Vitality; Softness; Dynamism; Harmony; Variety; Functionality	24	Semantic Differences Scale
Chen Ranpeng [23] (2022)	Visual comfort; park beauty; light color richness; ambient quietness; light ambience; light character; spatial experience coherence; nighttime visual luminance; sense of mood; environmental cleanliness; light color tendency; light coordination; history	13	Questionnaires and semi-structured interviews
Wang Yirui [30] (2020)	Physics dimension: Temperature and brightness Aesthetics dimension: The light source itself; Illuminated object; The expression form; Light form; Rhythm; Color Space dimension: Boundary sense; Domain sense; Direction sense Time dimension: Time changes; Seasonal changes Psychology dimension: Style atmosphere; Emotional experience; Cultural association	15	online questionnaire surveys

2. Description of Research Work

This study adopts a structured research framework comprising four sequential phases: problem identification, empirical case analysis, methodological application, and strategic derivation (Figure 1). Through this progression, the study systematically investigates the various types of lightscapes that exist in urban park environments during daytime hours and conducts a comprehensive evaluation of lightscape perception among park users.

By implementing this framework, the study not only delineates the typological characteristics of daytime lightscapes but also constructs an evaluative system that captures perceptual nuances across multiple dimensions. The framework is designed to ensure the scientific rigor and practical applicability of the research, thereby facilitating the development of targeted strategies for optimizing visual environments in urban parks.

3. Materials and Methods

3.1. Research Area

Shuixi Park, situated in the Xiqing District of Tianjin, encompasses approximately 140 hectares and ranks among the largest comprehensive urban parks in the city. Roughly 30% of the park’s area is composed of water bodies, while the remaining landscape features a diverse, stratified vegetation structure—comprising trees, shrubs, and groundcover—organized in a three-layer hierarchy. The terrain is topographically varied, interspersed with culturally significant landscape elements, such as viewing pavilions and sculptures, alongside open recreational spaces. Together, these features contribute to a multifaceted and dynamic lightscape interface. With an average daily visitation of around 5000 individuals spanning all age groups, the park functions as a typical public recreational space within the urban fabric. Since its inauguration in 2018, Shuixi Park has evolved into a key site for social interaction and leisure, embodying both natural and cultural attributes that shape its distinct landscape identity (Figure 2).

3.2. Semi-Structured Interview Survey

Organized interviews provide a valuable means of capturing residents’ authentic lightscape experiences within urban parks. Prior to the interviews, the research team categorized the various types of lightscapes present during the day in the park. This classification was based on the properties of visible light, identified through on-site observation, photographic records, and preliminary online surveys on light perception (

Table 2. Lightscape types in Shuixi Park.

Category	Specific Lightscape Types
Natural Direct Lightscapes	Sky light, sunset, shimmering water reflections, dappled light filtered through foliage
Natural Indirect Lightscapes	Cloud shadows, reflected vegetation in water, various shadows cast by flora, built structures, and even human or animal figures

).

To ensure the representativeness and objectivity of the interviews, the research team divided Shuixi Park into five zones based on landscape types (Figure 3). From February to June 2024, semi-structured interviews were conducted with residents across different zones of the park at various times and locations. To ensure accuracy, the interview framework was developed by analyzing relevant literature on factors influencing lightscape perception and considering the potential cognitive levels of park visitors. In addition to gathering basic demographic and perceptual information, the interviews focused on three key areas: the specific lightscape elements consciously perceived by respondents; subjective evaluations of the lightscape quality within Shuixi Park; and a range of behavioral activities potentially triggered by the lightscape environment (see Supplementary Materials).

A total of 51 residents participated in the interviews. Data collected included demographic attributes, perceptual responses, and behavioral tendencies (Figure 4). Preliminary analysis indicated a temporal distribution skewed toward afternoon visits. Although the sample featured a relatively high proportion of well-educated individuals, general awareness of the concept of lightscape remained limited. While most participants readily identified basic visual cues—such as skylight and vegetation—further researcher prompts revealed a latent sensitivity to subtler aspects, including the behavioral dynamics of others within the space.

3.3. Determining the Driving Elements and Evaluation System

Several factors influence lightscape perception. After reviewing the relevant literature on lightscape studies, it became clear that much of the research focuses on the discussion of environmental light characteristics, such as color and visual comfort [31,32], or the role of spatial atmosphere and space shaping in lightscape perception [23,33]. In contrast to traditional methods that overly emphasize the presentation and variation of light, this study also examines the information that light might convey, as well as the social, cultural, and spiritual characteristics of human responses to light environments [34]. These broader theoretical perspectives from environmental psychology and emotional landscape design also provide important background for understanding the perception of light landscapes [35,36]. Meanwhile, the interviews revealed that the “human” factor also significantly impacts lightscape perception [37,38,39], particularly in terms of individual behavior and emotional responses.

Based on these insights, expert consultations were used to determine the evaluation criteria, integrating the results from interviews and relevant data. By linking “human” as a connecting element, and considering environmental light characteristics, landscape spatial forms, and behavioral activities at Shuixi Park, the lightscape perception elements were categorized into three types: experiential, spatial, and social dimensions. After eliminating redundant indicators based on the on-site survey, the final evaluation framework covers these three dimensions—social, spatial, and experiential—as the foundation for constructing a comprehensive lightscape perception evaluation system.

This evaluation system is divided into three layers (

Table 3. Evaluation index system for perceptions of urban park scenery.

Goal Layer	Criterion Layer	Primary Indicator Layer	Secondary Indicator Layer	Conceptual Explanation
Evaluation index system for perception of urban park scenery	Social dimension	Emotional perception	Direct perception	Emotional contagion occurs through contact or dialogue between two parties.
			Indirect perception	Emotional contagion occurs when one witnesses the facial expressions and actions of others.
		Behavioral connections	Group affiliation	In park activity spaces, people tend to gather in groups unconsciously. For example, if they see others sunbathing, they will unconsciously lie down.
			Interactive behavior	Individuals engage in activities with certain group characteristics under certain conditions, such as conversation and games.
	Spatial dimension	Spatial elements	Topography and landforms	Types of roads within the park and characteristics of terrain changes
			Landscape vegetation	Various plants and flowers planted in the park
			Water features	Lakes, rivers, etc., within the park
			Buildings, sculptures, and structures	Landscape structures such as buildings, pavilions, towers, and sculptures within the park
		Spatial characteristics	Spatial visual orientation	Using visual landscapes to guide individuals’ movement and behavior in the environment, thereby creating different visual experiences.
			Spatial openness	Spaces with varying degrees of openness affect people’s visual experiences.
			Spatial sense of order	Spaces with a sense of order are more conducive to helping people establish visual perception.
	Experiential dimension	Scenic characteristics	Light color	Scene color representation and color vividness
			Dynamism	Static and dynamic changes in scenery
			Light sensitivity	The brightness of the scenery environment in the field of vision
			Continuity	The continuity or disorderliness of scenery changes
		Scenic rhythm	Sensory experience	The influence of other sensory experiences, such as hearing, smell, and thermal humidity, on scenery
			Weather variation	Refers to narrowly defined weather characteristics such as sunny, rainy, and cloudy days
			Seasonal variation	The four seasons of spring, summer, autumn, and winter throughout the year
			Temporal nodes	The three important time periods of morning, afternoon, and evening throughout the day

). The first layer is the goal layer, representing the urban park lightscape perception evaluation system. The second layer is the criterion layer, which includes social dimensions reflecting individual psychological activities and behavior characteristics; spatial dimensions that directly affect individual perception through static spatial carriers; and experiential dimensions describing the relationship between individuals and the light environment. The third layer consists of evaluation indicators, which are specific elaborations of the criterion layer. This includes both primary and secondary indicators, resulting in a total of 19 evaluation factors.

Based on the aforementioned evaluation framework, a panel of 21 experts from the School of Architecture at Tianjin University—comprising professionals in landscape architecture and related fields—was invited to assign weights to each evaluation indicator using a 9-point scale. The process involved the construction of pairwise comparison judgment matrices, the computation of weights under individual criteria, and the execution of consistency checks to derive the final weight set. The consistency check, a critical step in evaluating the coherence between the constructed matrix and its idealized counterpart [40], was conducted by calculating the Consistency Ratio (CR), following a four-step procedure:

Step 1: Calculate the maximum eigenvalue λmax of the decision matrix.

Step 2: Compute the Consistency Index (CI) using the formula:

$$\mathrm{CI} = {\displaystyle \frac{\lambda max-n}{n-1}}$$

(1)

where n is the order of the matrix.

Step 3: Calculate the Consistency Ratio (CR) using the formula:

$$\mathrm{CR} = {\displaystyle \frac{CI}{RI}}$$

(2)

where RI represents the Random Consistency Index.

Step 4: Compare the calculated CR value against the threshold of 0.1. If CR < 0.1, the judgment matrix is deemed to have acceptable consistency.

In this process, the closer the CI value is to zero, the higher the consistency of the matrix. The Random Consistency Index (RI) is introduced to assess the relative magnitude of CI and is presented in

Table 4. RI comparison table.

n	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.58	0.90	1.12	1.24	1.32	1.41	1.45	1.49

.

The resulting factor weights are summarized in

Table 5. Weight calculation results of the evaluation index system.

Goal Layer	Criterion Layer		Primary Indicator Layer		Secondary Indicator Layer
	Criterion	Weight	Primary Indicators	Weight	Secondary Indicators	Weight	Weight Sort
Evaluation index system for perception of urban park scenery	Social dimension	0.177	Emotional perception	0.308	Direct perception	0.400	0.022
					Indirect perception	0.600	0.033
			Behavioral connections	0.692	Group affiliation	0.333	0.041
					Interactive behavior	0.667	0.082
	Spatial dimension	0.284	Spatial elements	0.364	Topography and landforms	0.146	0.015
					Landscape vegetation	0.201	0.021
					Water features	0.328	0.034
					Buildings, sculptures, and structures	0.325	0.034
			Spatial characteristics	0.636	Spatial visual orientation	0.324	0.059
					Spatial openness	0.213	0.038
					Spatial sense of order	0.463	0.084
	Experiential dimension	0.539	Scenic characteristics	0.364	Light color	0.123	0.024
					Dynamism	0.235	0.046
					Light sensitivity	0.405	0.079
					Continuity	0.236	0.046
			Scenic rhythm	0.636	Sensory experience	0.167	0.057
					Weather variation	0.218	0.075
					Seasonal variation	0.218	0.075
					Temporal nodes	0.397	0.136

.

3.4. Evaluation of Light Perception Based on the Fuzzy Comprehensive Evaluation Method

The fuzzy comprehensive evaluation method is a mathematical technique based on fuzzy set theory [41,42,43,44], which enables the transformation of ambiguous or hard-to-quantify factors into measurable evaluations. This method allows for the quantification of qualitative elements within the assessment system through the use of membership functions, thereby bridging the gap between subjective experience and objective indicators [45,46]. The general procedure involves several key steps: first, the definition of an evaluation set V and a hierarchy of factor sets U, followed by the establishment of a fuzzy mapping from the factor set to the evaluation set. This mapping yields the fuzzy relation matrix R, which represents the degree to which each factor is associated with various evaluation outcomes. In this study, a five-point Likert scale [47,48] was employed to define the evaluation set V = {Satisfied, Relatively Satisfied, Neutral, Relatively Dissatisfied, Dissatisfied}, corresponding to numerical values from 5 to 1. The factor set U was constructed according to the structure of the evaluation system. Specifically, the criterion-layer factor sets U_i {i = 1, 2, 3} represent the three dimensions: social, spatial, and experiential. The indicator layer factor sets U_i,j (j denotes the specific sub-indicators associated with each dimension). For simplicity and computational efficiency, only the secondary indicators were included in the calculation; primary-layer factors were omitted. For example, U_1,1 represents direct perception, and U_3,6 corresponds to weather variation. The fuzzy relation matrix R contains the proportion of respondents selecting each satisfaction level for each indicator, expressed as a ratio of the number of responses per layer to the total number of respondents. In this study, R = {R₁ R₂ R₃}, where each R_i corresponds to one of the criterion-layer dimensions. R₁ = {R_1,1 R_1,2 R_1,3 R_1,4} and R_1,1 = {R_1,1,1 R_1,1,2 R_1,1,3 R_1,1,4 R_1,1,5}, where R_1,1 represents direct perception in the indicator layer; R_1,1,1 represents the proportion of environmental perception satisfaction score in the rating level.

Subsequently, the weight vector A, derived from the previously calculated indicator weights, is multiplied by the fuzzy relation matrix R to obtain the fuzzy comprehensive result vector B:

B = A × R

(3)

where B is the resulting evaluation vector and A is the vector of indicator weights.

Finally, defuzzification is performed on the result vector using a weighted average approach. By applying the score vector H = {5, 4, 3, 2, 1}, the comprehensive evaluation score E for the lightscape perception satisfaction in Shuixi Park is calculated as follows:

E = B × H

(4)

where H corresponds to the five satisfaction levels.

3.5. Sample Collection and Data Processing

Based on the previously established evaluation framework, a follow-up questionnaire survey was conducted in September 2024, targeting residents within the five designated zones in Shuixi Park. To ensure the scientific rigor, objectivity, and generalizability of the data, 40 questionnaires were distributed in each functional zone, covering respondents from diverse age groups, genders, education levels, and occupations (Figure 5).

A total of 200 questionnaires were distributed, with 177 valid responses collected, yielding an effective response rate of 88.5%. The questionnaire’s reliability and validity were statistically verified: Cronbach’s alpha coefficient was 0.939, indicating high internal consistency, while the KMO value was 0.903, signifying excellent construct validity. The aggregated results are shown in

Table 6. Index system for perception of urban park scenery.

Criterion Layer	Indicator Layer	The Proportion of Evaluators to the Total Number of People
		Satisfied	Relatively Satisfied	Neutral	Relatively Dissatisfied	Dissatisfied
Social dimension	Direct perception	0.316	0.316	0.294	0.062	0.011
	Indirect perception	0.305	0.322	0.311	0.051	0.011
	Group affiliation	0.243	0.249	0.305	0.124	0.079
	Interactive behavior	0.305	0.339	0.237	0.085	0.034
Spatial dimension	Topography and landforms	0.356	0.305	0.282	0.051	0.006
	Landscape vegetation	0.322	0.339	0.220	0.079	0.040
	Water features	0.401	0.345	0.136	0.056	0.062
	Buildings, sculptures, and structures	0.333	0.294	0.192	0.130	0.051
	Spatial visual orientation	0.328	0.350	0.237	0.062	0.023
	Spatial openness	0.446	0.367	0.153	0.017	0.017
	Spatial sense of order	0.294	0.407	0.169	0.079	0.051
Experiential dimension	Light color	0.322	0.362	0.249	0.056	0.011
	Dynamism	0.429	0.446	0.107	0.011	0.006
	Light sensitivity	0.435	0.446	0.113	0.006	0.000
	Continuity	0.379	0.407	0.198	0.017	0.000
	Sensory experience	0.305	0.401	0.175	0.096	0.023
	Weather variation	0.384	0.350	0.243	0.017	0.006
	Seasonal variation	0.384	0.333	0.209	0.051	0.023
	Temporal nodes	0.367	0.316	0.288	0.023	0.006

, representing the proportions of each satisfaction level selected for each indicator.

Using this data, the distribution of responses in the five satisfaction categories for each criterion-layer factor was calculated as follows:

$${\mathrm{R}}_1 = \left[\begin{array}{ccccc}0.316& 0.316& 0.294& 0.062& 0.011\\ 0.305& 0.322& 0.311& 0.051& 0.011\\ 0.243& 0.249& 0.305& 0.124& 0.079\\ 0.305& 0.339& 0.237& 0.085& 0.034\end{array}\right]$$

(5)

$${\mathrm{R}}_2 =\left[\begin{array}{ccccc}0.356& 0.305& 0.282& 0.051& 0.006\\ 0.322& 0.339& 0.220& 0.079& 0.040\\ 0.401& 0.345& 0.136& 0.056& 0.062\\ 0.333& 0.294& 0.192& 0.130& 0.051\\ 0.328& 0.350& 0.237& 0.062& 0.023\\ 0.446& 0.367& 0.153& 0.017& 0.017\\ 0.294& 0.407& 0.168& 0.079& 0.051\end{array}\right]$$

(6)

$${\mathrm{R}}_3 =\left[\begin{array}{ccccc}0.322& 0.362& 0.249& 0.056& 0.011\\ 0.429& 0.446& 0.107& 0.011& 0.006\\ 0.435& 0.446& 0.113& 0.006& 0.000\\ 0.379& 0.407& 0.198& 0.017& 0.000\\ 0.305& 0.401& 0.175& 0.096& 0.023\\ 0.384& 0.350& 0.243& 0.017& 0.006\\ 0.384& 0.333& 0.209& 0.051& 0.023\\ 0.367& 0.316& 0.288& 0.023& 0.006\end{array}\right]$$

(7)

Based on the calculated weights of each indicator, the fuzzy evaluation vectors B at the indicator level were derived. B₁ = {B_1,1 B_1,2 B_1,3 B_1,4 B_1,5} = {0.292 0.312 0.273 0.085 0.037}; B₂ = {B_2,1 B_2,2 B_2,3 B_2,4 B_2,5} = {0.344 0.359 0.190 0.069 0.039}; B₃ = {B_3,1 B_3,2 B_3,3 B_3,4 B_3,5} = {0.379 0.372 0.208 0.031 0.009}. Subsequently, defuzzification was applied to the criterion-layer evaluation sets using the following method:

Ei = Bi × H (i = 1,2,3)

(8)

Through weighted aggregation, the satisfaction scores Ei for residents’ lightscape perception in Shuixi Park were obtained across the three primary dimensions: social, spatial, and experiential. E₁ = 5B_1,1 + 4B_1,2 + 3B_1,3 + 2B_1,4 + B_1,5 = 3.737; E₂ = 5B_2,1 + 4B_2,2 + 3B_2,3 + 2B_2,4 + B_2,5 = 3.901; E₃ = 5B_3,1 + 4B_3,2 + 3B_3,3 + 2B_3,4 + B_3,5 = 4.082. Next, the comprehensive evaluation set W was calculated as follows: W = {W₁ W₂ W₃ W₄ W₅} = {0.354 0.358 0.214 0.051 0.022}. The final composite satisfaction score for lightscape perception in Shuixi Park was computed as follows: E = 5W₁ + 4W₂ + 3W₃ + 2W₄ + W₅ = 3.969.

4. Discussion

4.1. Stratified Evaluation Based on Statistical Results

According to the results of the fuzzy comprehensive evaluation, the overall lightscape perception satisfaction score for Shuixi Park is 3.969, which approximates the “relatively satisfied” level on the Likert scale. This indicates a generally high level of satisfaction among residents regarding the park’s lightscape quality. By comparing the scores across the three evaluation dimensions with the five-point Likert scale, a stratified analysis of resident satisfaction was conducted (Figure 6).

From the perspective of the criterion layer, the satisfaction scores across all three dimensions hover around 4.0, reflecting broadly favorable perceptions of lightscape experiences during park visits. Among these, the social dimension received the lowest satisfaction score, while the experiential dimension scored the highest, with the spatial dimension falling in between. These results suggest that dynamic aspects of the physical light environment most strongly influence lightscape satisfaction, followed by spatial landscape features, while sociocultural stimuli contribute comparatively less to perceptual impact.

At the indicator layer, the scores for the social dimension were consistently lower. Notably, the indicator for interactive behavior scored the lowest at 3.452. This finding suggests that the existing lightscape environment in Shuixi Park provides limited stimulation to encourage interpersonal interactions. Field observations corroborate this, revealing that although the park covers a vast area, it accommodates a relatively low daily population, thereby reducing the likelihood of spontaneous social encounters [49]. Furthermore, socially engaging spaces are primarily concentrated within a few zones, while most recreational areas lack the environmental cues needed to foster social interaction or prolonged stays. As a result, visitors tend to remain mobile and more focused on the surrounding environmental and individual perceptions, rather than engaging in collective behaviors [50,51].

In contrast, the spatial dimension demonstrated moderate satisfaction levels. Notably, elements such as water features and spatial openness yielded the highest ratings within this dimension. While varied topography, diverse vegetation, and architectural structures contribute to rich light-shadow interplay and enhance visual interest [5], prior research has consistently shown that public aesthetic preferences strongly favor aquatic elements [4,52]. Given that water bodies occupy approximately one-third of Shuixi Park’s total area, this preference is likely reflected in elevated satisfaction scores for hydrological features. In addition, the park’s heterogeneous spatial forms contribute to differential openness, enhancing the perceptual richness of the lightscape and reinforcing the high satisfaction associated with spatial openness.

In the experiential dimension, satisfaction levels were consistently high. Indicators such as seasonal variation and sensory experience exerted substantial influence. Through research, it was found that people generally appreciated the seasonal color dynamics of spring, summer, and autumn, whereas the monotony of winter scenes was viewed as a shortcoming, reflecting an underdeveloped approach to seasonal lightscape design. Furthermore, deficiencies in the park’s soundscape—such as excessive loudness and abrupt sound transitions [53]—negatively impacted the sensory experience. In contrast, Shuixi Park features diverse landscape spaces with rich layers, enabling more varied landscape changes triggered by climate or time [54], thereby achieving higher satisfaction levels.

4.2. Interrelationships Between Driving Elements

A comparative examination of the indicator scores (Table 5 and Table 6) and observed patterns in the field suggests that the individual elements within the lightscape perception system are not independent but function through complex interdependencies. The factors operate in a dynamic, synergistic manner, collectively shaping perceptual outcomes rather than acting in isolation. The following discussion synthesizes these qualitative patterns, supported by the existing literature, to illustrate how improvements in one dimension may influence others. For instance, increased diversity in spatial landscape features enhances the generation of varied lightscape phenomena. This, in turn, elevates the overall experiential quality, as visitors are exposed to a broader range of sensory stimuli. Enhanced experiential quality may also serve as a catalyst for social interaction, encouraging behaviors such as group conversation, passive engagement, or collective movement [55]. Thus, improvements in one dimension may propagate beneficial effects across others, creating a positive feedback loop that amplifies overall perceptual satisfaction.

Moreover, the strength of inter-element correlations varies. For example, a greater spatial openness directly enhances the emotional perception of light, often evoking feelings of comfort, tranquility, or visual release [56]. Simultaneously, well-defined spatial visual orientation not only strengthens the spatial logic and order of the environment but also improves the continuity of the visual and perceptual experience. This alignment across perceptual layers reinforces the user’s spatial cognition and enriches the narrative flow of their interaction with the landscape.

These findings affirm the importance of considering perceptual elements not as isolated metrics, but as part of an integrated system in which improvements to one factor may have ripple effects across others. Strategic interventions should therefore be developed with an awareness of these interrelations, enabling designers and planners to maximize perceptual quality through coordinated, multi-dimensional enhancements.

4.3. Lightscape Planning Process and Optimization Strategies

Drawing upon the evaluation results and the structured planning framework established earlier, this study proposes three strategic directions to optimize the lightscape quality of Shuixi Park from the standpoint of user-centered perception:

At the level of facility configuration enhancements, considering the spatial concentration of gathering functions and the low satisfaction with interactive behavior, it is recommended that shaded rest facilities be expanded—particularly within the “Viewing & Gathering Zone” and “Recreation & Sports Zone”. The introduction of such semi-sheltered spaces would enhance spatial retention, stimulate spontaneous social interactions, and diversify the functional attributes of these zones, thereby improving their accessibility and appeal to key user groups such as the elderly and children. In the “Contemplation & Rest Zone”, layering vegetation vertically can both increase lightscape variation and reinforce a serene, introspective atmosphere. Along the eastern and western “Lakeside Promenade”, the installation of semi-enclosed seating alcoves could enrich spatial rhythm and encourage lingering. Additionally, clusters of social seating elements would facilitate communal activities, contributing to elevated satisfaction in the social dimension.

Regarding the integration of functionality and sensation, design interventions that intensify light-shadow dynamics are key to enhancing experiential quality. For example, integrating translucent architectural structures—such as lattice pergolas—into linear paths can create dappled light effects, generating spatial–temporal variety. In densely vegetated zones, selective pruning of canopy layers can modulate light penetration and produce multi-depth visual textures composed of flickering light and layered shadows. Furthermore, enhancing water features at key nodes—such as park entrances and central plazas—through installations like fountains, streams, or cascading waterfalls can raise ambient humidity and enrich the acoustic landscape. These enhancements cultivate a multi-sensory environment where light, sound, and space interact cohesively to elevate the user’s perceptual experience.

In terms of environmental and seasonal adaptability, seasonal optimization strategies are also crucial. To mitigate the visual monotony characteristic of winter, designers should increase the use of evergreen plant species and integrate artificial scenic elements that offer color and structure year-round. During summer months, incorporating climbing plants such as wisteria onto hardscape surfaces can reduce glare, introduce thermal relief, and contribute to chromatic layering. Across all functional zones, introducing topographic variation and implementing multi-tiered vegetation schemes can enrich lightscape complexity. Along walking trails, clustered planting arrangements may create more nuanced light–shadow contrasts. Replacing uniformly spaced street trees with irregular spacing patterns can further enhance visual dynamism and promote naturalistic aesthetics.

5. Conclusions

A scientifically constructed lightscape perception evaluation system serves as an essential analytical tool for guiding the design, renovation, and optimization of urban park lighting environments. Nevertheless, the inherent complexity and multidimensionality of such indicator systems often obscure the pathways by which evaluation outcomes may be effectively translated into design interventions. This disconnect poses a critical barrier to the enhancement of perceptual and environmental quality in built landscapes.

To address this challenge, the present study proposes a human-centered evaluation framework grounded in the dynamic interplay between individuals, spatial environments, and lighting conditions. By incorporating the dimension of resident behavioral activity and leveraging the strengths of fuzzy comprehensive evaluation methodology, the study introduces an integrative approach that bridges subjective perception with quantitative analysis. Applied to the context of Shuixi Park in Tianjin, this framework yields several key conclusions:

(1)

Experiential indicators exert the most significant influence on lightscape perception among the three evaluated dimensions, while the social dimension demonstrates comparatively weaker effects. This suggests that dynamic and environmental light qualities play a more prominent role in shaping user satisfaction than sociocultural stimuli.

(2)

Among the driving factors, light sensitivity and spatial openness emerged as the most responsive elements influencing residents’ perceptual experiences. In contrast, spatial features such as topography showed relatively limited impact.

(3)

Targeted design strategies, particularly those oriented toward facilitating social engagement—such as the introduction of interactive facilities—are essential for improving perceptual outcomes within underperforming dimensions, especially the social layer.

Despite its contributions, the study is subject to certain limitations. First, the sample size and subjective nature of expert evaluations may constrain the generalizability of the proposed system. Future research should seek to diversify both participant and expert samples and to replicate this evaluation framework in multiple parks and regions to facilitate external comparison and enhance the robustness of findings. Secondly, some findings, such as the relative influence of light sensitivity and spatial openness, are based on descriptive observation rather than statistical testing. Future research should employ quantitative analytical methods to confirm these relationships. Furthermore, this research focuses exclusively on daytime lightscapes, without addressing perceptual responses to nocturnal lighting environments. Future research will expand the dataset through multi-site collaborations and include additional parks to establish a city-wide lightscape evaluation database. This expansion will enable more nuanced, scalable, and locally adaptive planning strategies. Second, it must be acknowledged that urban park lightscape planning is a complex and systemic endeavor. While identifying perceptual elements provides valuable theoretical guidance, practical implementation must also account for local economic conditions, temporal dynamics, and regional adaptability. The evaluation framework introduced here has the potential to be applied across a broader range of urban park contexts. However, future adaptations should consider the recalibration of indicator weights to better align with local priorities—for example, placing increased emphasis on winter lightscape resilience in northern climates.