Suitability Evaluation of Architectural Images Built in Communities Based on the Niche-Fitness Model

Abstract

Architectural images, experienced visually and spatially, embody urban culture, aesthetics, and identity, yet their suitability in urban communities remains underexplored. This study addresses this gap by evaluating the suitability of architectural images using the niche-fitness model, combined with residents’ perception assessments. Evaluation indicators focus on architectural form, color, features, and values to assess how well buildings align with residents and environmental contexts. The findings reveal significant variations in suitability across six studied buildings in a high-density community in Wuhan. One building showed high ecological adaptability and alignment with residents’ functional and aesthetic preferences, while others exhibited moderate to low suitability, reflecting mismatches with residents’ perceptions. The inharmonious adaptability of these buildings demonstrates the need to harmonize architectural images with residents’ psychological preferences to enhance community livability and identity. Combining Wuhan’s regional characteristics, suggestions for improving the governance of architectural images are proposed to address mismatches. This study analyzes the role of architectural image suitability in improving residents’ quality of life and shaping urban community characteristics. By offering a practical approach for guiding the renewal of architectural images in communities, this research contributes to creating livable and culturally resonant environments to support sustainable urban development.

1. Introduction

Architectural images play a vital role in shaping community identity, urban culture, and city aesthetics [1]. As key elements of a city’s visual and spatial fabric, they are increasingly valued in modern urban planning [2]. However, rapid urbanization has led to the proliferation of high-rise buildings, resulting in homogenized cityscapes and inconsistent quality of urban architectural images [3]. This has created a pressing need to renew old buildings and establish a cohesive architectural style that reflects regional identity and cultural continuity. In response, China’s 2023 urban renewal policies emphasize improving the environmental quality of old communities while preserving urban character and historical context. The renewal of architectural images is crucial for the rational transformation of old buildings, improving urban image, and creating livable environments [2]. Micro-renewal of architectural images has emerged as a key strategy for fostering residents’ sense of belonging and happiness, enhancing the image and appeal of cities [4,5]. However, effectively transforming architectural images to meet these goals remains a significant challenge.

The evaluation of architectural image suitability provides a new perspective for solving these challenges and formulating improvement strategies. Understanding the relationship between architectural images and residents’ living experiences contributes to enhancing the aesthetic value of architectural images in community landscapes and urban culture. As reflections of residents’ well-being—including livability and quality of life—architectural images should align with the overall landscape of the area, forming a harmonious relationship with surrounding buildings. Post-construction evaluations can reveal residents’ satisfaction with architectural images based on their perceptions and experiences. However, traditional evaluation often focuses narrowly on functionality, neglecting cultural, perceptual, and psychological dimensions. There is limited research on assessing the suitability of architectural images, particularly in community settings.

To address this gap, this study proposes integrating ecological adaptability with architectural images and evaluating suitability by identifying and resolving mismatches between the built architectural images and residents’ living and psychological preferences. This approach will help the architectural images to meet functional needs and resonate with the cultural and emotional expectations of a community.

1.1. Literature Review

1.1.1. Conceptual Foundations of Architectural Image

Architectural image is a professional term rooted in architectural and aesthetic theories. Ten Books on Architecture first proposed that the architectural image conforms to the general laws of aesthetics [6,7]. As one of the three core elements of architecture—alongside architectural function (the structural purpose) and architectural technology (the enabling means)—architectural image serves as the comprehensive reflection of both [7,8,9,10]. The modern architecture movement in the 20th century has made people understand that architecture should meet both the material and spiritual needs of human beings [11,12]. Therefore, architecture’s visual expression and symbolic meaning have gradually attracted attention. Pioneers of modernist architecture, such as Le Corbusier and Walter Gropius, departed from traditional design methods and embraced new materials, technologies, and ideologies. They proposed that the orientation, composition, combination, and other forms of expression of architectural images are metaphors for corresponding functional effects and aesthetic meanings [13,14]. Subsequently, the concept of the architectural image was gradually enriched. Most scholars believe that the architectural image refers to the appearance and internal quality of a building through its design, structure, materials, and other elements [10,15,16,17,18]. Simply speaking, the architectural image is the embodiment of the internal and external perception of a building [18,19].

1.1.2. Components of the Architectural Image

The architectural image can be represented by a series of measurable attributes, namely indicators, broadly divided into visual and non-visual elements [14,20,21]. So, the architectural image can be regarded as an organic combination of these elements. The compositions of architectural images are illustrated in Figure 1.

On the one hand, architectural images refer to the overall visual perception and impression a building conveys [22]. They are represented by visual elements such as architectural form, facade composition, details and decoration treatment, material texture, light and shadow, and color application [23,24]. Specifically, (1) architectural form shaped by elements like shape, proportion, volume, and direction, defines the outline and appearance of a building. It also governs the combination, separation, and transition of internal and external space, forming the foundation of architectural images [25,26,27]. Architectural form and spatial layout reflect the uniqueness and unity of architectural images in both indoor and outdoor environments. (2) Color and texture are vital components of architectural images, adding vividness and layering while directly influencing visual perception and emotional experience. Colors convey emotional atmospheres and cultural connotations through materials like paint, stone, and glass [28,29]. Texture refers to the tactile and visual characteristics of building materials, such as roughness, smoothness, hardness, and softness [27]. (3) Decoration and detail processing play a key role in improving building images. Decoration design includes wall, floor, and ceiling treatments, as well as the selection and arrangement of interior furnishings [27]. Fine decoration highlights a building’s style and characteristics, creating a comfortable and aesthetically pleasing indoor environment. Details like door and window design further enhance architectural images [27]. Architecture is a comprehensive art form, embodying aesthetic and artistic value through its planes, elevations, color, texture, and the integration of indoor and outdoor spaces [30,31]. The image of contemporary architecture extends beyond aesthetics, emphasizing functionality and interaction with the environment [15]. For example, Sapienza (2014) explored how innovative technologies shape architectural images [32], while Stănculescu (2014) examined their impact on the evolution of museum architecture [33]. Zayats and Murgul (2015) highlighted practical elements like rainwater systems as both functional and decorative features [34]. Permyakov and Krasnova (2020) proposed that modern architectural design and construction should integrate physical and social public spaces, enhancing urban security through architectural images [35].

On the other hand, architectural images encompass non-visual elements such as cultural connotations, historical background, and social value. They provide spiritual enjoyment through aspects like form, space, color, texture, and details [9,10]. The spirit and meaning in architecture are increasingly important, as architectural images profoundly shape urban characteristics and identity, influencing people’s impression and perception of the city through style, scale, and layout. Thus, urban architecture images reflect a city’s nature and function [36], shaped by regional culture, social spirit, and the national style of a city in a specific era. Scholars have discussed the role of architectural images in conveying meaning and revealing local idioms [37,38]. Jin and Liu (2013) emphasized designing architectural images based on regional characteristics, enhancing urban charm through form and color [36]. Architectural design integrates function, structure, and technology to ensure harmony with surrounding spaces and promote diversification [39]. Zhu and Chen (2011) highlighted the importance of architectural images in preserving and restoring Buddhist temples [40], while Ciaburro et al. (2020) and Nie et al. (2020) analyzed the regionality and mutual learning of ancient architectural images [41,42]. Smith et al. (2021), Zheng (2021), and Adams and Hill (2022) discussed the evolution of urban architectural images through the integration of classical and modern culture amid social changes [43,44,45]. Mba et al. (2024) noted that regional differences and cultural characteristics foster unique architectural images, emphasizing their role in urban planning, cultural heritage protection, and the application of green technologies and materials [39].

Thus, architectural imagery conveys artistic style and unique charm while reflecting the geographical environment, cultural context, and social needs. The components of urban community buildings in the image dimension provide a critical foundation for studying index factors in architectural image evaluation.

1.1.3. Evaluation Methods

Architectural images can be reflected in residents’ evaluations and satisfaction with community buildings, influencing their perception and judgment of the city’s image. Architectural image evaluation is complex due to the interplay of endogenous and exogenous indicators. Existing research has proposed methods such as fuzzy mathematics, multi-criteria decision models, and the Analytic Hierarchy Process (AHP). Since some indicators cannot be quantified numerically and require expert judgment, AHP, which incorporates subjectivity, is particularly useful [46,47,48]. AHP enables clear prioritization and is effective in situations where differing opinions hinder optimal decision-making. However, most studies focus on decision-making methods and program evaluation in architectural image design, architectural efficiency, and construction project bid evaluation [49,50,51]. Few studies have quantitatively evaluated architectural images.

This paper introduces ecological niche theory to quantitatively assess the suitability of community-building images. Niche theory, particularly Hutchinson’s n-dimensional hypervolume hypothesis [52], represents the variation in a species’ suitability across an n-dimensional spatial region [53,54]. The concept of niche fitness, defined as the closeness between a species’ real ecological site and its optimal ecological site, characterizes the suitability of a species to its habitat [52,55,56,57]. The niche-fitness model, proposed by Chinese scholar Li Zizhen in 1997 [58], has been applied across various fields, including crops, natural resources, human settlements, innovative ecosystems, tourism, and urban construction [59,60,61]. Although ecological theory is increasingly applied in architecture, few studies have used the niche-fitness theory to evaluate architectural images. Buildings can be viewed as species occupying different times, spaces, and resources, with natural and social factors influencing architectural images regarded as ecological elements [59]. Accordingly, this paper defines the suitability of urban community architectural images as the closeness between the real ecological niche of architectural images and the optimal ecological niche. It reflects the gap between the current state of community architectural images and residents’ ideal conditions, representing the degree of alignment between building images and residents’ living environment demands.

1.2. Research Aims and Main Contents

This research aims to bridge ecological theory and architectural practice, offering a reference for improving architectural images in urban communities. In this study, images of six high-rise buildings in a high-density residential community in Wuhan were taken as the objects. Their suitability was quantitatively assessed with selected indicators based on the niche-fitness model. The alignment between current architectural images and residents’ living preferences was analyzed to reveal the livability of the settlement. Finally, practical guidance for optimizing building images and enhancing the urban community environment is provided according to the results.

This study supports community image renewal and provides actionable insights for urban planners and policymakers, by promoting sustainable and coordinated development in architectural image dimensions. These insights ensure that architectural renewal aligns with environmental sustainability and human-centered design principles to enhance residents’ quality of life, and preserve the unique identity of cities in an era of rapid urbanization.

2. Materials and Methods

2.1. Study Area

Wuhan, a national historical and cultural city in central China, is an important birthplace of Chu culture and is committed to building a high-quality urban image as a national central city [62]. As a rapidly developing megacity with a highly dense population, Wuhan faces challenges in improving the quality of the human settlement environment, particularly in high-rise, high-density communities [63]. The renewal of old, high-density communities requires significant attention. This study focuses on six buildings in a high-rise, high-density community built in 2014 within Wuhan’s urban area. These buildings share similar structures and forms. Over the past decade, the outer walls of the buildings have begun to deteriorate, and spatial details have been adjusted to meet residents’ demands for environmental quality. However, as living standards rise, residents’ expectations for improved architectural and community images have grown significantly. Architectural images, which shape community identity and influence residents’ sense of belonging and happiness, are increasingly prioritized. There is a need to assess these buildings’ image suitability to address these evolving needs. The location of the studied community is shown in Figure 2.

2.2. Index System Construction

2.2.1. Selection of Evaluation Index for Suitability of Architectural Image

This paper takes function and personalization as the evaluation basis, technical specification as the bottom line of the evaluation standard, and residents’ aesthetics and vision as the evaluation criterion to construct the evaluation index system of the architectural image. Based on the component analysis of architectural images in the literature review, evaluation indicators were selected from two aspects: visual and non-visual elements. In this paper, the concept of ecological niche fitness was integrated with ecological factors such as spatial composition and scale that influence architectural images. Meanwhile, building standards and norms, including the certification system of DGNB (Deutsche Gesellschaft für Nachhaltiges Bauen e.V.), the sustainable assessment framework Sustainable Project Appraisal Routine (SpeAR), the Green Building Tool (GBTool 1.3), the LEED (Leadership in Energy and Environmental Design), the BREEAM (Building Research Establishment Environmental Assessment Method), the CASBEE (Comprehensive Assessment System for Building Environmental Efficiency), and the relevant literature [64,65,66,67], were referenced. Moreover, the subsequent principles are followed to construct the evaluation index system: (1) indicators for architectural image evaluation should be representative, scientific, and practical; (2) visual elements should embody the harmonious coordination between architectural images and the urban community living environment; and (3) non-visual elements should embody historical and cultural values through measures like the excavation and display of local cultural heritage. Ultimately, a three-tier index system for evaluating architectural image suitability was established (see

Table 1. Evaluation index system for the niche fitness of the architectural image.

Objective	First-Level Factors	Second-Level Factors	Interpretation	Reference
Suitability of architectural image A	Visual elements B1	Aesthetics of architectural form C1	Aesthetic effect reflected by the external form of a building designed to meet residents’ demand for visually appealing effects.	[15,24]
		Architectural color effect C2	Comforting effect of a building’s color atmosphere, created through floor plan and facade design, to enhance occupant comfort.	[24,27]
	Non-visual elements B2	Embodying local architectural features C3	The reflection of local architectural characteristics, traditions, and humanistic environment in a building.	[13,15]
		Embodying historical and cultural values C4	The embodiment of historical culture, humanistic information, and age-specific style characteristics, including historical figures, events, scientific and technological knowledge, and leisure entertainments, within a building.	[15,19]

).

Specifically, the first layer is the overall evaluation of architectural images as the target layer. The second layer, namely the criterion layer, is considered from two aspects: the architectural form and color (B₁) and the local architectural features and historical value (B₂). The third layer is the factor layer and contains four factors: aesthetics of architectural form (C₁), architectural color effect (C₂), embodying local architectural features (C₃), and embodying historical and cultural values (C₄). In the aspect of element B₁, it reflects residential building images in the spatial pattern of a community, emphasizing the integration of a building with its surroundings through external aesthetics. Residents’ perceptions capture the coordination and impression of a building within the overall community environment. Architectural form, as a human-created spatial expression, and the atmosphere generated by color collocation and application, imbue architecture with rich emotional expression and connotation. Therefore, element B₁, which reflects spatial expression and emotional connotations conveyed by color, is determined by C₁ and C₂. In the aspect of element B₂, it focuses on how community architecture can preserve, adapt, and reflect the humanistic environment, showcasing the human spirit and cultural implications through non-visual elements. This includes local construction styles, distinctive characteristics, and historical culture, embodied in the architectural image dimension. Therefore, element B₂ can be determined by C₃ and C₄. The evaluation index system of architectural images is summarized in Table 1.

2.2.2. Determination of Index Weights

The weight coefficients were determined alongside the construction of the evaluation index. For decision-making problems with fewer evaluation indicators, the Analytic Hierarchy Process (AHP) is an effective subjective weighting method. AHP breaks down complex problems into a hierarchical structure, using expert judgment and pairwise comparisons to assign weights. It systematically integrates evaluation indicators while considering relationships within and between levels, and addresses the limitations of overly mathematical or binary approaches. By calculating the judgment matrix, AHP weighs indicators and makes decisions based on ranking results through analysis, judgment, and synthesis. Its ability to describe internal dependencies of elements and incorporate expert scores ensures a balanced evaluation. With a small number of indicators in this study, AHP is practical and effective for determining weights in the evaluation of architectural image suitability based on its many advantages. Therefore, this paper applies AHP to reasonably weigh the evaluation indicators.

As a method relying on expert judgment, AHP has inherent limitations. Subjective factors in scoring indicators and comparing them on a 1–9 scale can lead to discrepancies due to differing expert knowledge and values. Additionally, imprecise processing of the judgment matrix allows subjective judgments to significantly influence results. To address these limitations, we combined AHP with the Delphi method to determine weights, using group judgment and the mean aggregation method to reduce subjective bias and enhance objectivity. The combined AHP–Delphi method incorporates measures such as expert input, structured criteria development, and consistency checks, as detailed in Figure 3. These steps aim to mitigate subjectivity, minimize deviations, ensure balanced evaluations, and enhance reliability.

Meanwhile, multiple experts were selected to determine the importance of pairwise indicators and construct the index judgment matrix. In this paper, these experts were drawn from administrative, technical, and research departments, with over 10 years of experience and intermediate or higher professional titles. Specifically, 10 experts with extensive architectural image research experience and 20 practitioners experienced in architectural design, construction, or community renovation were invited to rate the judgment matrices. The selection criteria and expert sources are detailed in

Table 2. Sources and selection criteria for experts.

Expert Sources	Selection Criteria	Number of Experts
Researchers	Associate professor or professor engaged in architectural design research for more than 10 years	10
Practitioners	Senior architecture engineer with more than 10 years of practical work in building construction	20

.

Moreover, to streamline the tedious and repetitive calculations of AHP and improve accuracy, we used Super Decisions (SD, v2.10, William J. Adams, USA) software, developed by AHP founder, Professor Saaty. The software helped construct the structural model based on correlations and calculated weight coefficients. A multilevel hierarchical structure was established for indicators C₁–C₄ in Table 1. Using the 1–9 scale method in SD, the relative importance between factors was measured and compared to determine dominance degrees. The maximum eigenvalue and eigenvector of the judgment matrix were calculated by the square root method, and the consistency of the matrix was tested. The results of the expert questionnaire were input into the software to calculate local relative weights for factors, which were then combined with first-layer weight coefficients to obtain aggregate weights for architectural image evaluation indicators. The index weights are shown in

Table 3. Weights of evaluation indicators.

First-Level Factors	Weight	Second-Level Factors	Local Weight	Aggregate Weight	Ranking
B1	0.8413	C1	0.7222	0.6076	1
		C2	0.2778	0.2337	2
B2	0.1587	C3	0.7674	0.1218	3
		C4	0.2326	0.0369	4

.

2.3. Data Acquisition

Score data for each index were obtained through an actual investigation based on the subjective perceptions of community residents. Architectural images and their group combinations are administered to the subjective feelings and judgments of community residents. If residents perceive the architectural image negatively, their sense of residential happiness and belonging may decline. Conversely, a positive architectural image can enhance occupants’ enthusiasm and satisfaction. Since the suitability evaluation of architectural images, composed of multiple elements, relies heavily on community residents’ intuitive perceptions, a scoring method was used to quantify qualitative indicators with specific numerical values.

A marking table was designed and used for data collection to evaluate the suitability degree of architectural images in the community environment (seen in

Table 4. Evaluation criteria of indicators involved in architectural image.

Indicators	Evaluation Criteria
	[9, 10]	[7, 9)	[4, 7)	[0, 4)
C1	Very beautiful	Beautiful	Neutral	Ugly
C2	Very good	Good	Neutral	Bad
C3	Fully embodying	Relatively embodying	Basically embodying	Insufficiently embodying
C4	Very high	Relatively high	Neutral	Not high

). Scoring table items are adapted from the suitability evaluation indexes, with ratings on a 10-point scale and four comment grades corresponding to the ranges of 0–4, 4–7, 7–9, and 9–10. Critical values of the index scoring criteria were determined based on research scales studied by scholars, existing standard specifications, and the principle of relative optimality. Meanwhile, a descriptive statement at the bottom of the scoring table assisted residents in evaluating architectural images. Before releasing the scoring table, we conducted expert interviews, inviting experts as mentioned above to assess the questionnaire and make necessary revisions to ensure its reliability and validity. The revised scoring table was used in 40 pre-surveys, and further improvements were made based on the pre-survey findings to finalize the questionnaire.

The finalized table was used to investigate residents of the six buildings on-site, with 60 residents surveyed per building, totaling 360 responses. If a questionnaire was invalid, the survey was repeated until a valid response was obtained. Sample data were collected through quantitative scoring, with investigators providing explanations of relevant background and concepts when necessary. The survey was conducted in two field sessions during winter and spring. Finally, the weighted average method was used to calculate the scores of the suitability evaluation indicators in the image dimension for each building in the community.

2.4. Niche-Fitness Calculation for Architectural Images

2.4.1. Calculation of the Single-Index Niche-Fitness Value

The first-layer ecological index, composed of second-layer ecological factors, can be regarded as one dimension of architectural image evaluation. The multi-dimensional space formed by these ecological factors serves as an evaluation unit. Within each unit, the niche-fitness value represents the single-factor niche fitness to be calculated. Niche-fitness theory, originally applied to biological units, is adapted here to measure the suitability of each evaluation unit for specific architectural images factors, quantified by a suitability index. When an evaluation factor or unit meets the demand condition, the niche-fitness value of the architectural image in the factor direction is 1. When an evaluation unit completely fails to meet the demand condition, the niche-fitness value is 0 [58]. Visibly, niche-fitness values range from [0 to 1], with higher values indicating better adaptation [58]. Since niche fitness reflects the suitability of existing conditions for development needs, architectural images seek to find suitable niches that maximize profits effectively. Therefore, calculating the niche fitness of architectural images is essential for identifying the strengths and weaknesses of different ecological factors within a community ecosystem.

Niche-fitness values of evaluation factors or evaluation units are calculated to quantify architectural images. The quantitative indicators of selected ecological factors for architectural image evaluation can be marked as x₁, x₂, …, x_n. The evaluation values of each building in the image dimension can be denoted as an n-dimensional ecological vector: X_r = (x_r1, x_r2,…, x_rn), which indicates an actual state of the architectural image under certain community residents’ demands. X_r can also be viewed as a point in the n-dimensional factor space that is noted as Eⁿ. Moreover, X_r ∈ Eⁿ, and Eⁿ = [x_ij]_m×n, with i = 1, 2, …, m, and j = 1, 2, …, n. Here, x_ij represents the actual state of ecological factor j for the i-th building in the image dimension. The formula for calculating the niche-fitness value of an architectural image is shown in Equation (1).

$$N{f}_i={\displaystyle \sum _{j=1}^n{\beta }_j\frac{\min \left\{\left|x_{ij}-x_{aj}\right|\right\}+\epsilon \cdot \max \left\{\left|x_{ij}-x_{aj}\right|\right\}}{\left|x_{ij}-x_{aj}\right|+\epsilon \cdot \max \left\{\left|x_{ij}-x_{aj}\right|\right\}}} (i=1,2,\dots ,m; j=1,2,\dots ,n)$$

(1)

where Nf_i denotes the niche-fitness value of dimension i in the architectural image within the human settlement space, with Nf_i ∈ [0, 1]. A larger Nf_i indicates a higher satisfaction degree of the current architectural image with residents’ requirement, and a closer alignment between the status quo and demand. β_j represents the weight of ecological factor j in the architectural image dimension, with ${\displaystyle \sum _{j=1}^n{\beta }_j=1}$. x_ij represents the i-th value of ecological factor j, while x_aj (where j = 1, 2, …, n) represents the optimal value of niche fitness for the ecological factor j in the special architectural image dimension. ε (where 0 ≤ ε ≤ 1) is a model parameter, and its estimation formula is as follows.

$${\displaystyle \frac{\min \left\{\left|x_{ij}-x_{aj}\right|\right\}+\epsilon \cdot \max \left\{\left|x_{ij}-x_{aj}\right|\right\}}{\overline{{\delta }_{ij}}+\epsilon \cdot \max \left\{\left|x_{ij}-x_{aj}\right|\right\}}}=0.5$$

(2)

$$\overline{{\delta }_{ij}}={\displaystyle \frac{1}{m\cdot n}}{\displaystyle \sum _{i=1}^m{\displaystyle \sum _{j=1}^n\left|x_{ij}-x_{aj}\right|}}$$

(3)

(1)

Determination of the optimum value of niche fitness for the elements

Niche-fitness measures the adaptation degree of different dimensions involved in architectural images to residents’ requirements, based on the proximity between ecological factors. The niche-fitness value of an architectural image is calculated based on the relative deviation between the actual value x_ij and the optimal value x_aj. This illustrates the ecological resource configuration required for architectural image development and highlights the advantages, weaknesses, and adaptability of a building within its habitat for a given dimension. According to niche-fitness theory, each subdivision indicator typically has an optimal value for the architectural image grade [52,58]. The indicators in the index system of suitability evaluation for architectural images used in this paper are efficiency-based. For benefit-based indicators, a higher evaluation value corresponds to a more favorable assessment of the architectural image grade by residents, which also supports the sustainable development of architectural images. An ecological factor’s maximum value represents its ideal standard for the perceived quality of human settlements. The formula can be expressed as:

x_aj = max{x_ij}

(4)

where x_aj and x_ij have the same meaning as mentioned above. Therefore, for indicators of architectural image evaluation, the maximum score of 10 is confirmed as the optimum value to calculate the niche fitness of different evaluation units in this study.

2.4.2. Calculation of the Comprehensive Niche-Fitness Value

Individual indicators can reflect the suitability of one aspect, whereas the comprehensive index method can integrate scattered individual information for the whole evaluation object of an architectural image [68]. Based on the index weight W_j corresponding to ecological factors in Table 3, the weighted average method is used to calculate the comprehensive suitability of architectural images composed of subdivision dimensions. The comprehensive niche-fitness evaluation reflects the adaptability of building image to meet residents’ needs. The formula for calculating the comprehensive niche-fitness value, that is the suitability of an architectural image, is as follows:

$$SUI={\displaystyle \sum _{i=1}^m{W}_{i}N{f}_i} (i=1,2,\dots ,m)$$

(5)

where $SUI$ represents the comprehensive value of niche fitness for an urban community building in the image dimension; W_i represents the weight value of the i-th suitability index contained in architectural images; Nf_i represents the niche-fitness value of urban community buildings in the sub-dimension habitat of the i-th index included in the comprehensive dimension of architectural images; m represents the number of ecological indicators in the integrated dimension of the niche hypervolume structure, which serves as the building image evaluation unit. The closer the suitability value is to 1, the higher the alignment between the architectural image and residents’ requirements. Furthermore, a larger suitability value indicates stronger and superior adaptability of the architectural image within the human settlement habitat. A high degree of coordination and satisfaction between the architectural image and residents’ needs promotes the expansion of the architectural image dimension, such as renovation and renewal. In summary, the comprehensive suitability of architectural images reflects the overall situation of evaluation indicators in urban communities, identifies key influencing factors, and helps assess residents’ satisfaction with architectural images.

3. Results and Discussions

3.1. Niche Fitness of Single Index

Residents’ evaluation values of the architectural image across various dimensions were obtained through the survey, and the average values were calculated (see

Table 5. Residents’ perception and evaluation scores on building images.

Evaluation Index		C1	C2	C3	C4
Comprehensive weight		0.6076	0.2337	0.1218	0.0369
Local weight		0.7222	0.2778	0.7674	0.2326
The mean of evaluation index scores for each building	b1	4.83	6.2	3.35	0.86
	b2	6.35	7.28	5.31	1.12
	b3	5.76	6.04	3.67	1.05
	b4	6.12	6.51	6.29	0.98
	b5	5.27	5.85	2.56	0.64
	b6	6.61	8.16	3.14	1.18

below). Using the weights of the secondary indicators, these mean values were input into the formulas for single-dimensional suitability calculation.

Based on the statistical data obtained from field research, Equations (1)–(4) were used to calculate the suitability of each building’s architectural image. Niche-fitness values in the first-level dimensions were calculated using the actual scores of ecological factors for buildings 1–6 in the second-level dimension. The evaluation indicators share the same attribute type, with a maximum evaluation value of 10, a minimum of 0, and an optimal value of 10 for each. The scoring values of each indicator were substituted into the model to calculate the sub-dimensional suitability of buildings 1–6 using Formulae (1)–(3). The suitability of the first-level factors among buildings 1–6 was compared, and the results are shown in Figure 4. The mean niche-fitness values of the six architectural images in dimensions B₁ and B₂ were calculated as 0.5004 and 0.6076, respectively, with a grand mean value of 0.5540. Accordingly, the suitability value distribution of these six buildings, centered around their means, is illustrated in Figure 5.

3.2. Suitability Ranking

The matching between the actual architectural image and residents’ demand was assessed using the niche-fitness model. Comprehensive niche-fitness values were calculated based on the niche-fitness values of single-factor indicators and the weights of first-level indicators. Using the weight of each evaluation index (see Table 3) and the niche-fitness values at the first level, the comprehensive niche-fitness values of buildings 1–6 in the architectural image dimension were calculated using Equation (5). The results, determined by the suitability calculation formula, are shown in Figure 6, which illustrates the suitability distribution characteristics of buildings 1–6 in the settlements.

3.3. Discussion

3.3.1. Suitability of Architectural Images Based on the Niche-Fitness Model

(1)

Evaluation result analysis for subdivision dimensions

According to Figure 4, the matching relationship between the niche-fitness values and community residents’ requirements is analyzed in the dimensions of ecological factors that constitute the architectural image. Firstly, in terms of architectural image and color dimension (B₁), the niche-fitness values of the evaluated community buildings in B₁ dimension are Nf_b6(0.6766) > Nf_b2(0.5612) > Nf_b4(0.4985) > Nf_b3(0.4519) > Nf_b5(0.4133) > Nf_b1(0.4006), with an average value of 0.5004. It can be seen that the niche-fitness value of Building 6 is the highest in the B₁ dimension, indicating that Building 6 has a high degree of satisfaction for residents in the modeling and color dimension of the architectural image. This is followed by Building 2. The niche-fitness values of the other four buildings in dimension B₁ are all less than 0.5. Among them, the niche-fitness value of Building 4 is close to 0.5, which is 0.0466 more than that of Building 3 in this dimension. However, the niche-fitness values of Buildings 5 and 1 are both close to 0.4, indicating that these two buildings have poor suitability in dimension B₁ and satisfy residents’ needs to a low degree.

In terms of the expression of architectural historical and cultural value and architectural culture (B₂), the niche-fitness value of each building in the assessed community in this dimension is ranked as Nf_b4(0.8641) > Nf_b2(0.7075) > Nf_b3(0.5506) > Nf_b1(0.5270) > Nf_b6(0.5173) > Nf_b5(0.4793), with an average value of 0.6076. It can be seen that the suitability of Building 4 is the highest, indicating that Building 4 has a high degree of satisfaction for residents in the dimension of the historical and cultural value of architectural image. Building 2 follows. The niche-fitness values of Buildings 3, 1, and 6 in this dimension are close to each other, indicating that residents are generally satisfied with these three buildings in this dimension. Finally, the niche-fitness value of Building 5 is less than 0.5, indicating that Building 5 meets residents’ needs to a low degree in the B₂ dimension.

According to Figure 5, the distribution of niche-fitness values for six buildings across two elevation dimensions, B₁ and B₂, along with their mean values and the grand mean, highlights the general performance of the community’s architectural images. First, in terms of the niche-fitness values, they range from 0.4006 to 0.8641, indicating varying levels of suitability for architectural images within the community. Moreover, buildings with higher values, such as Nf_b4 in dimension B₂, demonstrate better adaption to the ecological factors, while lower values, like Nf_b1 in dimension B₁, suggest mismatch and areas needing improvement. Second, in terms of dimensions, the suitability of architectural images in dimension B₂ generally falls on higher values compared to dimension B₁. Half of the buildings exceed the composite average of 0.5540 in the B₂ dimension, while four buildings fall below the grand value of 0.5540. This suggests that residents prioritize visual elements, such as building form, color, and texture, over non-visual elements, like cultural value, in their evaluations. This finding aligns with Maslow’s hierarchy of needs theory [69], indicating that residents’ current functional demands for buildings outweigh their spiritual demands. It also means that, although community transformation in China has entered a new stage of image alteration [70], improving basic functional needs, such as infrastructure and green spaces, remains a top priority. Therefore, future renewal efforts should continue to emphasize visual elements while gradually incorporating non-visual elements as residents’ perceptions evolve.

(2)

Analysis of comprehensive evaluation results

According to Figure 6, the suitability of architectural images is analyzed as follows. In the studied community, the comprehensive niche-fitness values of architectural images for buildings 1–6 differ greatly. The comprehensive values for the six buildings’ architectural images are ranked as SUI_b6(0.6513) > SUI_b2(0.5844) > SUI_b4(0.5565) > SUI_b3(0.4676) > SUI_b5(0.4238) > SUI_b1(0.4206), with an average value of 0.5174. Visibly, this indicates a lack of coordination in the suitability of these six buildings in the architectural image dimension. Among them, Building 6 has the largest comprehensive niche-fitness value in architectural image, indicating good adaptability. Moreover, the index factors, serving as resources, satisfy the functional demands of Building 6 to a high degree, enhancing its recognition and satisfaction among residents. This is followed by Building 2 and then Building 4. In contrast, Buildings 3, 5, and 1 have comprehensive suitability values below 0.5, with Buildings 5 and 1 both nearing 0.42. Building 1 has the smallest value, indicating poor adaptability to ecological factors and low satisfaction with image resources for functional needs. These buildings require effective adjustments and improvements. Additionally, the incoherent rating of architectural styles implies finding a harmonious solution through multi-party negotiation in future renewal efforts.

3.3.2. Strategy Analysis for Architectural Image Development

Preliminary development plans and measures can be established according to the suitability evaluation of architectural images in communities. Architectural image evaluation reflects the satisfaction of building users, with variations in how index factors affect the niche fitness. By realizing the complementary strengths of architectural images and crafting integrated development strategies accordingly, the collaboration and reinvention capabilities of the entire community can be enhanced. Meanwhile, urban architecture provides residents with the enjoyment of visual beauty and unique artistic images. The style orientation and the inheritance of history and culture in architectural images are determined by influencing factors such as shape and scale. A building’s image should guide and integrate with the neighbor landscape to complement each other [23,67]. Essentially, the comprehensive evaluation results reflect the adaptation of architectural image dimensions to residents’ satisfaction. Niche theory supports the synergistic and sustainable development of architectural image in communities. Furthermore, the suitability of architectural images for community buildings is significantly influenced by residents’ preferences, and there is often incongruity in the suitability of architectural images across buildings. Therefore, residents’ perspectives should be prioritized in community planning. Different ideas and approaches can be adopted to improve architectural images.

By applying the niche-fitness theory, this study offers a practical framework for guiding the renewal of architectural images in urban communities, providing actionable insights for urban planners and architects. Recommendations for enhancing architectural image suitability contribute to sustainable urban development. The following countermeasures are put forward in this paper.

First, the reconstruction of architectural images in communities requires a long process of evolution, accumulation, and precipitation. The factors that effectively define architectural image attributes constitute key areas for improving community building images. The main factors influencing architectural image suitability are constantly adjusted to promote the ongoing evolution of the community. The improvement of architectural images reflects residents’ needs and enhances community environments, ensuring that changes align with their preferences and contribute to a more livable and harmonious urban space.

Implementing this recommendation requires long-term planning, community engagement, and iterative feedback mechanisms. Resources such as funding for participatory design workshops and time for residents to adapt to changes are essential. Challenges include balancing diverse resident preferences and ensuring consistent progress over time.

Second, optimizing the architectural image needs to highlight the key points. The suitability assessment reveals unbalanced development in the community’s architectural images, with Building 4 performing significantly better than Building 6. Therefore, renewal efforts should focus on buildings with strong foundations, leveraging their comparative advantages to further optimize architectural images.

This approach is resource-efficient, as it prioritizes buildings with existing potential. However, it requires detailed assessments to identify key areas and allocate resources effectively. Challenges include ensuring equitable improvements across the community and avoiding neglect of underperforming buildings.

Third, optimizing the architectural image requires endogenous motivation and cultural empowerment. The improvement of architectural images requires diversity, self-organization and coordination to maximize effectiveness. Ecological factors such as historical and cultural values are highly empowered and become the main bearers of current community architectural images, reflecting residents’ evolving requirements. Therefore, promoting these factors is essential to drive architectural image development.

This recommendation relies on leveraging local cultural and historical resources, which can be cost-effective and community-driven. However, it requires collaboration with cultural institutions and residents to ensure authenticity and relevance. Challenges include preserving cultural integrity while adapting to modern needs.

Fourth, the optimization of architectural images requires integration and symbiosis. A healthy architectural image should foster continuous interaction and integration between community residents’ requirements and ecological factors. The interplay of shape, color, function, and technology can unlock greater potential. Communities should create environments that encourage the free flow of ecological elements and promote coordination between buildings and communities through systemic and policy-driven approaches.

A diversified and efficient system relies on communication and cooperation between actors and the frequency of ecological factor flow. This approach requires interdisciplinary collaboration and policy support to create a cohesive framework. Resources include funding for integrated design projects and time for stakeholder consultations. Challenges include overcoming bureaucratic hurdles and ensuring sustained engagement from all actors.

4. Conclusions

This paper introduced niche theory and applied the niche-fitness model to evaluate the adaptability of buildings in the architectural image dimension. An empirical study was conducted using the geometric proximity of n-dimensional space for six residential buildings in a high-density urban neighborhood. The suitability of architectural images was evaluated and compared by calculating niche-fitness values. The results show significant differences in the suitability of the six buildings in the settlements, indicating opportunities to improve livability, social adaptability, and the realization of residential functions in the architectural image dimension. This research is a new attempt to evaluate the architectural image from the perspective of ecological niche. This study has its limitations, particularly in the establishment of the indicator system, and the lack of time-series data on residents’ preferences for architectural image suitability evaluation.

Future research can explore the following aspects: (1) the evaluation index system established in the architectural image dimension can be further expanded, with weights adjusted according to regional characteristics. Meanwhile, the selection of architectural image evaluation indicators should reflect a people-oriented concept, ensuring that community architectural images are attractive, functional, and socially and economically rational. (2) Given the diversity and complexity of architectural images under different socio-economic and technological contexts, future studies should explore the internal influence mechanisms of new technologies on architectural images, avoiding superficial imitation through creative design thinking and methods. (3) The suitability evaluation of architectural images should account for residents’ diverse preferences, influenced by geographical, historical, cultural, educational, age, and gender factors. Future research should explore the correlation between residents’ attribute characteristics and architectural image suitability, emphasizing the collection and analysis of residents’ preferences through surveys, interviews, and participatory design approaches. (4) External factors, including socio-economic indicators and the real estate price index, that may influence architectural image suitability can also be further expanded, combined with time-series data on residents’ preferences.