Grid-Based Characterization and Sustainable Planning for Fractured Urban Textures: A Case Study of Nanhao Village in Baotou

Abstract

During urban development, significant contrasts between urban villages and their surrounding areas lead to the emergence of fragmented urban spaces, dysfunctionalities, cultural barriers, and, ultimately, to the formation of fractured urban textures centered on urban villages (FUT-UVs). The fractured urban textures of an FUT-UV create a disconnect from the surrounding urban area, isolating it from the city. This separation significantly impacts the daily lives and interactions of its residents. To address this and support more sustainable urban development, a thorough and multi-dimensional understanding of FUT-UVs is of crucial importance. This study examines Nanhao Village in Baotou City, conducting a quantitative analysis of key indicators related to buildings, roads, and functional facilities. Using overlay analysis, it explores the characteristics of the FUT-UV, the interactions between these indicators, and opportunities for improvement. From these findings, strategies for reconnecting an FUT-UV with its surroundings are proposed. The results indicate that: (1) FUT-UVs are mainly characterized by low-rise, high-density developments with limited open space. Their road networks are narrow and congested, while accessibility remains low. Low-end businesses are concentrated in a single area within the village, showing minimal functional diversity; (2) FUT-UVs can increase construction intensity by raising the number of floors in buildings, and have higher building densities in the most accessible areas. This increase in density can effectively enhance functional diversity; and (3) improving road accessibility in FUT-UVs will allow for a smoother influx of external activity, enhancing functional diversity. Additionally, increasing the number of building floors intensifies construction, raises the density of functional facilities, and boosts urban vitality. Based on these characteristics of fragmentation and interactive mechanisms, this study suggests stitching strategies related to transportation, architecture, and functionality. This study introduces a new framework for analyzing urban texture, offering a detailed multi-faceted analysis of FUT-UV fragmentation and clarifying the interaction between FUT-UVs and surrounding urban forms. This study reinforces the coherence of the spatial form and the development of the functional economy of urban villages within the modern urban environment. It supports the sustainable development of urban areas and promotes balanced growth between urban villages and their surrounding regions.

1. Introduction

Urbanization is an unstoppable phenomenon, with projections indicating that by 2050, 68% of the world’s population will be living in urban areas [1]. Since its reform and opening-up, China has rapidly urbanized, leading to a significant expansion, reorganization, and transformation of its urban spaces, altering both their physical forms and internal functions. As cities grow and transportation systems become more complex, the urban texture—once defined by spatial continuity and consistency—is disrupted [2]. This fragmentation undermines the city’s overall coherence, fosters a sense of isolation among residents, and hinders the sustainable development of the urban district.

Amidst this rapid urbanization, China has witnessed the emergence of a unique phenomenon known as the urban village. These villages are experiencing significant spatial fragmentation and reorganization [3], evolving from natural villages to marginal villages, and, finally, to urban villages [4]. While retaining their village homesteads [5], urban villages see surrounding farmland expropriated to accommodate the ever-expanding urban areas [6]. As living spaces, urban villages maintain traditional social networks based on familial and geographic ties [7], yet they struggle to adapt to modern lifestyles and are losing their social and economic appeal [8]. The rapid urban development in surrounding areas disrupts villagers’ continuous connection to, and control over, their surroundings, leading to physical, environmental changes, disrupting local attachments, and necessitating cultural adaptation [9]. This development also sparks severe conflicts with the surrounding urban texture, architectural style, and scale, resulting in fragmented urban spaces, dysfunctional areas, cultural barriers, and deteriorated living conditions. Consequently, this triggers a cycle of relentless decay [4].

Taking Nanhao Village in Baotou City as an example, this study examined urban texture fracture, focusing on ’Fractured Urban Textures Centered Urban Villages’ (FUT-UVs). Through a combined methodology of a literature review, semi-structured interviews, and field investigations, the study identified and analyzed various factors contributing to this texture fracture both within FUT-UVs and their surrounding urban areas. The study utilized a geographic information system (GIS) to conduct grid sampling of quantitative indicators related to material elements, such as architectural features, road networks, and functional facilities, in FUT-UVs and their surrounding urban areas. Subsequently, the collected data underwent visualization and statistical analysis. A superposition correlation analysis was then conducted using a graded matching approach to explore interactive mechanisms between the FUT-UV and the physical elements of surrounding urban areas. Finally, a stitching and reconstruction strategy was developed for the FUT-UV, including design interventions for the fracture zones of urban texture centered around Nanhao Village in Baotou City. The specific aims of this research are as follows: (1) to explore the influencing factors and manifestations of FUT-UV; (2) to analyze internal issues within the FUT-UV and its interaction mechanisms with surrounding urban areas, providing quantitative support; and (3) to extract strategies for stitching urban texture integration and integrate these into the design of Nanhao Village in Baotou City.

2. Literature Review

2.1. Spatial Renovation of Urban Villages

The renewal and transformation of urban village spaces significantly impact urban development and residents’ well-being, playing a crucial role in city renewal [10]. Research on this topic primarily focuses on the following four aspects: the intrinsic spatial value of urban villages; the internal industrial economy; the social organizational structure; and the overall urban development system.

Urban village spaces nurture the value of social vitality [11]. By preserving traditional spatial mechanisms and cultural contexts [12,13], these areas enhance public spaces, improve quality of life [14], and create innovative spaces [11], emphasizing the creation of micro-scale spaces and highlighting the role of material environment transformation in reshaping community emotions [15,16]. The economic activities within urban villages yield significant social benefits, which have been studied through methods like semi-structured questionnaires [17], behavioral annotation, and GPS tracking, revealing spatial patterns in informal manufacturing [18] that optimize functional formats [19] and enhance cultural industries [20]. Cohesive social organizations within urban villages should leverage their self-organizing capabilities to improve informal housing provision [20,21] and manage key stakeholders effectively [22,23]. By focusing on cultural revitalization and social networks, they can strengthen community capital and sentiment [12,24,25]. Regarding the development of the overall urban system, inclusive governance principles [26] and diverse transformation models [27] can address dual land-management conflicts, while district-wide planning and whole-village redevelopment strategies [28] achieve comprehensive solutions that benefit both urban village interests and city development [29,30].

2.2. Fractured Urban Textures

Fractured urban textures, based on the “Lost Space” proposed by Roger Trancik in 1986 [31], refer to areas that exhibit fragmented and alienated textures as a result of the collision between new and old urban elements. These areas, arising from varying degrees of roughness, tend to develop more slowly and have less vitality as a consequence of the impacts caused by such fracturing. When the texture of a modern city fractures, urban villages—due to their small scale, limited functions, and scarce resources [32]—are particularly vulnerable. This vulnerability leads to a decline in regional vitality and economic downturns, resulting in areas known as FUT-UVs.

With the rapid development of modern cities, many urban areas that are integral to daily life are becoming increasingly monotonous and impersonal [33]. In response to this fragmentation phenomenon, research primarily focuses on the following two aspects: the causes of urban fragmentation; and its manifestations in urban morphology. Fragmented urban spaces are seen as carriers of fragmented social relations [34,35,36,37]. The following five major factors contribute to their emergence: contemporary architectural design movements; ongoing urban renewal; ongoing planning policies; encroachment by private interests; and the use of land replacement in old cities [38]. Research on the fragmented nature of urban areas primarily focuses on qualitatively describing [39,40] urban morphology, particularly in relation to public spaces [41,42,43].

2.3. Urban Texture Approaches and Methodologies

Current research on urban texture primarily employs techniques, such as urban network analysis [44], space syntax [45,46], and percolation theory [47], to study how individual elements, like buildings, streets, and public spaces, evolve and interact within urban morphology. The material elements within the urban texture evolve over time, spontaneously creating order within the chaos, both in their individual forms and interrelationships [47,48]. Urban texture is considered a complex system with connectivity rules, interaction forces, and a hierarchical organization [49], allowing for a layered analysis. Its formation follows similar principles to other complex systems [49]. Additionally, the network structure of urban texture is closely linked to its functionality [50], influencing urban vitality [51,52].

Distinct from the traditional urban morphology perspective, which relies on the hierarchical structure of buildings, plots, and streets, another approach views urban texture as an aggregate of various sample units analyzed through grid sampling. This method allows for an in-depth study of the relationships between the sample units and the overall structure. For example, Yang Chen et al. [53] used the XGBoost model to evaluate the significance of urban spatial form indicators at 10 grid scales, considering landscape patterns, architectural morphology, and social development. Jilong Zhao et al. [54] employed a grid-based method to visually determine urban grain-related spatial indicators, including building density, road density, building structure age, the width of street-facing building façades, the number of street-facing entrances, and functional mixing. Xi Wang et al. [55] applied a multi-source data and city meta unit (CMU) data model to explore key aspects of urban land use distribution, patterns, and composition. The grid-based sampling analysis of urban texture favors integrated multi-factor analysis. For instance, Qiong Luo et al. [56], using Wuhan as a case study, applied a grid-based method to quantify human settlement needs with 26 spatial and non-spatial indicators, establishing a community livability assessment. Ye Yu et al. [57] categorized and matched various sample unit indicators from different urban textures using spatial syntax, spatial matrix, and functional mix models.

Grid-based sampling analysis allows for a visual representation of the differentiation between different material elements; their overall attributes can be derived through a detailed study of numerous individual sample units. Furthermore, this type of analysis can correlate multiple elements by leveraging overlaps within the same sample unit, integrating quantitative outcomes across various elements.

3. Materials and Methods

3.1. Study Area and Analytical Framework

3.1.1. Study Area

This study analyzed urban texture fragmentation in 67 areas with FUT-UVs in Baotou through field visits, satellite mapping, and literature comparisons (Figure 1). Based on the diverse morphologies of FUT-UVs, the fragmentation manifestations of FUT-UVs were categorized into the following three primary types: point-like; linear; and areal (Table 1).

Nanhao Village is situated in the Rare Earth Hi-tech Industrial Development Zone of Baotou City, Inner Mongolia. Located centrally in Baotou, it possesses abundant resources, a dense population, and substantial development potential [58] (Figure 2). Nanhao Village was established in the late Qing Dynasty and early Republic of China by immigrants from Shanxi, Shaanxi, Hebei, and other regions [59]. Over time, the village has undergone substantial changes, leading to pronounced fractures in both its urban texture with the surrounding urban areas and the spatial texture within different sections of the village itself, reflecting a typical example of an areal FUT-UV. Nanhao Village boasts a unique architectural streetscape and vibrant living environment, showcasing cultural and lifestyle scenes distinct from its surrounding urban area. Spanning over 0.5 square kilometers, the village accommodates a floating population exceeding 23,000, surpassing its registered population. Figures S1 and S2 in the Supplementary Materials illustrate the building texture and urban form of the Nanhao Village area.

3.1.2. Analytical Framework

The FUT-UVs suffer from roughness and a lack clarity in their texture. The spatial and material elements, including architectural forms and road networks, of both the FUT-UV and the surrounding urban areas influence the FUT-UV. Concurrently, urbanization also enhances the urban morphology surrounding the FUT-UV, stimulating urban vitality. The fracture of the urban texture between FUT-UVs and their surrounding areas is analyzed through the following three dimensions: architectural form; road network; and human behavioral activities. This study captures the complexity of the relationship between these three dimensions of the urban texture in terms of architectural elements, road elements, and functional facility elements.

Building on previous research, this study introduces a novel framework consisting of four main steps (Figure 3): (1) The data acquisition, processing, and sampling cover a 3 km × 3 km area centered around Nanhao Village, using a 150 m × 150 m grid system to create 400 sample units for grid-based analysis; (2) The study extracts three material elements: architectural elements, road network elements, and functional facility elements. Using a grid-based sampling approach, these elements are quantitatively analyzed; (3) An overlay and correlation analysis is conducted based on the spatial autocorrelation of various material elements, with the aim of elucidating the degree of spatial-based associations among different material elements; and (4) Based on the correlation and interaction among various material elements, an exploratory design for FUT-UVs is proposed.

3.2. Data Source

Building vector data: Building vector data were extracted from the 2024 urban building outline data provided by the Resource and Environmental Science Data Center of the Chinese Academy of Sciences, and were further refined and calibrated in terms of building stories based on the actual field research conducted on 20 April 2024.

Construction land data: Construction land data were based on the 2018 Baotou city’s vector data of construction land obtained from Mapping Essential Urban Land Use Categories in China (EULUC-China) [60]: Preliminary Results for 2018.

Street vector data: Street vector data were collected from the OpenStreetMap website on 1 May 2024 to acquire the urban road network data.

POI data: POI data for Nanhao Village and surrounding urban areas in 2024 were obtained via the Amap API. After cleaning and integration, 9188 POIs were selected, covering 18 categories, including, as follows: food and beverages; tourist attraction; public facility; enterprises, shopping; transportation service; finance and insurance service; science/culture and education service; motorcycle service; auto service; auto dealers; auto repair, daily life service; commercial house, sports and recreation; medical service; accommodation service; and governmental organization and social group.

3.3. Data Preprocessing

In this study, the ArcGIS 10.8 platform was employed for spatial analysis during data preprocessing. To integrate data from various material elements, these elements were processed into a standard grid. Considering the scale of Nanhao Village and the surrounding urban texture, a 150 m × 150 m grid was chosen, totaling 400 grids. The 3 km × 3 km area encompassing Nanhao Village and at least one adjacent urban block served as the macro-scale study of the impact of texture fractures on cities and villages. Meanwhile, the 150 m × 150 m sample units facilitated meso- and micro-scale analyses of the fracture characteristics within the urban village and their interactions with the surrounding urban texture. To investigate the impact of FUT-UVs on urban areas, this study classified 20 sample units that included the village as the Nanhao Village region. This allowed for a comparative analysis with the surrounding urban sample units, providing a deep analysis of FUT-UV effects on urban areas.

3.4. Quantification Indicators for Single Material Elements

The fracture characteristics of FUT-UVs are reflected in architectural elements, road elements, and functional facility elements, with eight characteristic indicators selected for further analysis, including, as follows: (1) Architectural elements focus on the spatial dimensions and sense of scale in neighborhoods and buildings. This study selected three indicators: the floor area ratio, building density, and the average number of floors; (2) Road elements pertain to the accessibility of a district. This study selected two indicators: road density and road accessibility; and (3) Functional facility elements refer to the dominant functional types of a district, as well as the degree of diversity among these functional types. This study selected three indicators: functional density, functional mix, and the functional diversity index.

The well-defined measurement indicators in the index system, such as development intensity and building density, were quantitatively analyzed using the ArcGIS 10.8 platform for basic data processing. Abstract measurement indicators underwent preliminary quantitative processing. The quantitative methodology of the indicator system is shown in Table 2.

3.5. The Integrated Overlay Correlation Analysis Method

This study used a quantitative graded-value zoning matching method to analyze the correlation among material elements [61]. Using the natural breaks method [62], the values of comparative sample units for different material elements were classified into graded value zones from 1 to 5. The degree of matching between the sample units of different material elements was assessed by comparing the correlation of the graded value ranks of various elements on sample units located at the same spatial position. This method enables a detailed comparison of the matching relationships between different indicators and elements, as well as the correlation between FUT-UVs and their surrounding urban areas.

Specifically, the values of sample units for elements A and B are classified into grade values ranging from 1 to 5 using the natural breaks method. The absolute differences between their respective grade values at the same spatial position are calculated to compare their differentiation results. When the sample unit data for two elements fall within the same level, a value of 0 indicates a precise match. If the levels are adjacent, a value of 1 represents an approximate match. When there is a significant disparity, such as one element being at the maximum level and the other at the minimum, a value of 4 signifies a significant mismatch. The matching rate, calculated as the ratio of the combined number of precise and approximate matches to the total number of comparisons, indicates the positive correlation between the two elements. A higher matching rate signifies a stronger correlation (Figure 4, Table 3).

4. Results

4.1. Quantification of Single Material Element

4.1.1. Road Elements

Analyzing road density indices, Nanhao Village exhibits a higher road density compared to surrounding urban areas, with a 22% greater proportion of high road-density sample units. Road accessibility in Nanhao Village is relatively low and similar to that of the surrounding urban areas. Generally, internal road density and accessibility within urban villages exhibit opposing trends. Despite the presence of a dense internal road network, accessibility remains poor. This indicates that urban villages possess a relatively independent growth system and maintain a degree of isolation from surrounding urban areas, rendering them less susceptible to the influence of external urban areas (Figure 5). Table S1 in the Supplementary Materials presents the specific road element indicators for each sample unit in the Nanhao Village area.

Nanhao Village exhibits significant variation in road density, which is especially pronounced in the north and south. Streets in Nanhao Village are 7–9 m wide with a 1:1 width-to-height ratio; however, they face heavy congestion due to illegal construction and indiscriminate parking, severely limiting pedestrian space. Alleyways leading to doorways within Nanhao Village are 3–5 m wide, with a width-to-height ratio of 2–3 in the southern area, creating slightly cramped passages and leading to many dead-end roads. Surrounding urban roads, such as Xinguang East Road and JingyeAvenue, are interrupted by Nanhao Village, causing multiple cul-de-sacs.

4.1.2. Architectural Elements

Based on the architectural indices in Nanhao Village and its surroundings, the floor area ratio within Nanhao Village is significantly lower, with a higher proportion of low-intensity construction sample units. The average number of floors notably declines, with most buildings having fewer floors. Conversely, building density increases, particularly in the north and south sections of the village. This indicates that the textural fractures within architectural elements of urban villages exert a significant impact on the floor area ratio, building density, and the average number of floors. Compared to surrounding urban areas, the floor area ratio, and the average number of floors, in urban villages decrease overall, while the building density increases significantly (Figure 6). Table S1 in the Supplementary Materials presents the specific architectural element indicators for each sample unit in the Nanhao Village area.

In the northern and southern sections of Nanhao Village, the high number of buildings and increased building density create a compact texture with limited open spaces. In contrast, the central area is fragmented due to demolition and land acquisition in the early 2000s, resulting in irregular building arrangements and a lack of defined roads. Many buildings in the northern and central regions feature traditional courtyard layouts. The village’s building patches are generally small, blending structures from various historical periods. Moreover, texture gaps at intersections with urban roads contribute to the lack of urban fragments. Both the densely populated northern and southern areas, along with the abandoned central region, face challenges in identifying spaces conducive to human activities, highlighting a lack of vibrancy in the urban texture.

4.1.3. Functional Facility Elements

While the overall functional density in Nanhao Village mirrors that of surrounding urban areas, there is a notable increase in both high and lower functional density sample units compared to these areas. This indicates a pronounced functional concentration in Nanhao Village, particularly in the southern section. Urban villages have significantly less functional mixing and functional diversity than their surrounding urban areas, leading to limited spatial vitality. This highlights the need to enhance the diversity of functional activities (Figure 7). Table S1 in the Supplementary Materials presents the specific functional facility element indicators for each sample unit in the Nanhao Village area.

The kernel density analysis of various functional categories in Nanhao Village reveals a dissonance between its Sports and Recreation, Medical Services, and Culture and Education Services, and the corresponding facilities in the surrounding urban areas. Nanhao Village lacks professional medical institutions, having mainly healthcare facilities. Educational services are limited to a single kindergarten, and sports and leisure facilities are scarce (Figure 8).

Commercial service facilities in Nanhao Village develop relatively independently, showing an uneven distribution and homogeneous service offerings, leading to a dissonance with the surrounding urban areas. The village’s industrial structure is simplistic, and centered on low-end accommodation, dining, and basic services, resulting in the lack of a diverse clientele and the momentum for sustainable growth. Dominated by small vendors and lacking diversified industrial support, commodity trade in Nanhao Village results in slow economic and social progress. The village’s economy suffers from insufficient modern management, marketing strategies, and diverse industries, failing to meet residents’ employment and income needs. This leaves it vulnerable to market and policy changes, hindering sustainable development (Figure 9).

4.2. Multi-Factor Overlay Analysis

This study identifies architectural and road elements from FUT-UVs and surrounding urban areas as factors of urban spatial form. It also uses POI data as an indicator of urban functional vitality. Building on the method outlined in Section 3.5, this study analyzes the spatial relationships between the urban form elements of FUT-UVs, the surrounding urban areas, and urban functional vitality, assessing their degree of correlation and disconnection. Supplementary Material Tables S2 and S3 display the specific grades and grade differences for each sample unit in the Nanhao Village area.

The floor area ratio and average number of floors in the urban village match at a rate of 100%, similar to those in surrounding urban areas. However, the combined matching rates between building density and the floor area ratio or the average number of floors are notably low at 20%, significantly lower than those in surrounding urban areas. This suggests that in FUT-UVs, architectural form primarily boosts construction intensity through taller buildings, rather than through increasing building density. Although road density matches building density comparably in urban villages and surrounding urban areas, the correlation between road density and the floor area ratio or average number of floors drops significantly. This suggests that most roads within FUT-UVs are located in areas with lower construction intensity and fewer stories. The correlation between road accessibility and the floor area ratio or average number of floors in urban villages is weak (Figure 10, Table 4). Most areas with high accessibility have high building density but relatively low floor area ratios and floor counts, indicating an underutilization of road accessibility and the potential for increased construction intensity.

Whether viewed holistically or partially, there is no significant correlation between functional density and the degree of functional mix or the functional diversity index. Additionally, there are numerous sample units that are extremely mismatched. The comparison shows that sample units with a grade difference of 4, marked by high functional mix and low functional density, are mainly in the southern part of the village. Here, low functional density and high functional mix meet residents’ needs for functional diversity. The matching rate between functional mix and functional diversity is 100%, indicating a strong correlation.

In the urban village area, functional density shows a strong correlation of 70% with both floor area ratio and the average number of floors. However, its correlation with building density is comparatively lower, at only 40%. This indicates that the distribution of POIs in these areas does not align well with the high building densities present. There is a notable correlation between the functional mix or functional diversity index and building density in urban villages, contrasting with a much lower correlation with the floor area ratio or average number of floors when compared to surrounding urban areas. The increasing building density suggests that increasing building density effectively boosts functional mix and diversity. In the urban village, there is a strong correlation between functional density and road density, exceeding that of surrounding urban areas by 10%. However, the correlation between functional density and road accessibility is low, with a 35% matching rate, indicating that utilizing road accessibility for functional businesses in these areas requires improvement, and urban vitality in highly accessible zones remains underutilized. In the urban village, there is a low correlation between functional mix/functional diversity index and road density/accessibility, with a matching rate of 50% (Figure 11, Table 5). Although a high level of functional mix and functional diversity enhances urban vitality within these areas, inefficient use of road accessibility confines vitality to a self-sufficient state within a limited area, thereby failing to stimulate broader urban vitality.

In FUT-UVs, the high building density necessitates increasing floor levels to strengthen construction intensity. Moreover, enhancing functional diversity, business variety, and road accessibility typically involves increasing building density. Considering the spatial form of FUT-UVs, building density within these areas reaches its maximum. Restructuring the road hierarchy to improve vehicular and pedestrian flow can enhance local accessibility, leveraging transportation to attract external vitality and diversify business offerings. Increasing the number of building floors appropriately can increase the floor area ratio and the density of functional facilities, thereby enhancing urban vitality.

The vitality of FUT-UVs depends on utilizing high road density to attract external activity and a dense network to guide pedestrian flow, promoting urban liveliness. By transforming interstitial spaces at the edges of FUT-UVs and internal open areas into new public spaces and activity hubs, and integrating these with internal traffic, circulation and activity within these spaces are improved, thereby enhancing functional diversity and stimulating urban vitality.

5. Discussion

As urban development progresses, the efficient use of spatial resources becomes increasingly important, making FUT-UVs a key focus for urban renewal and sustainable development. Based on this, this study introduced a new framework for quantitatively analyzing urban texture, with a focus on understanding the characteristics of FUT-UVs and their interactions with material elements in neighboring urban areas. Additionally, it proposes corresponding design strategies.

5.1. Theoretical Contributions and Practical Implication

The emergence of FUT-UVs has disrupted the cohesion of urban areas [63]. The fragmented urban texture not only shapes the spatial form but also influences various aspects of city life, affecting residents’ lifestyles [64]. To foster the sustainable development of cities, this study focuses on clarifying the interaction between urban villages and surrounding areas. This study addresses a gap in the existing research, which has primarily focused on the value of urban villages themselves, neglecting the interaction between FUT-UVs and surrounding areas [65,66,67]. Additionally, previous studies on fragmented urban textures have mainly relied on qualitative descriptions of their current conditions and morphological characteristics, lacking objective, multi-index, quantitative analysis [39,40]. This study utilized ArcGIS 10.8 software to apply distinct tools and methodologies to accurately quantify various material elements, which were then compared and analyzed based on their spatial locations. Through grade-matching, specific and exceptional sample units were identified as priority targets for attention and optimization. Spatial splicing theory can reconcile and reorganize the fragmented urban fabric [68]. Building on the interaction mechanisms between FUT-UVs and surrounding urban areas, this paper proposes a strategy for integrating roads, buildings, and functions. This approach aims to enhance urban vitality and foster a more cohesive urban environment.

To address the complexity of FUT-UVs and their surrounding urban forms, a quantitative analysis method based on overlapping material elements in urban texture provides an objective and accurate understanding of their spatial characteristics. Analyzing the correlations among different material elements surrounding FUT-UVs enhances our understanding of infrastructure urbanization and illuminates how urban vitality flourishes. The FUT-UV stitching strategy, guiding FUT-UV renewal, offers practical methods to tackle urban texture fragmentation, resolves key challenges in current renewal efforts, and offers insights applicable to other FUT-UVs.

5.2. Countermeasures

By analyzing the interaction between Nanhao Village and the surrounding urban areas, this study highlights the connection and dynamic relationship between FUT-UVs and the urban texture of neighboring areas. The continuous promotion of transportation and urban development and construction stimulates urban vitality and ensures the sustainable development of the city. This study proposes policy recommendations and stitching design strategies focusing on roads, architecture, and function.

5.2.1. Road Texture Stitching

(1) Planning controls seek to create an organic connection between FUT-UVs and the city. Compared to the surrounding urban areas, FUT-UVs show notable differences in building density, road accessibility, and functional distribution. To reduce these differences, it is necessary to conduct overall planning for FUT-UVs based on the urban pattern. For instance, the government implements zoning and housing policies, extends the urban axis into FUT-UVs, connects the internal axis to the urban axis, and organizes key nodes. This will significantly improve the city’s overall image and quality, boosting the region’s attractiveness and competitiveness.

Using Nanhao Village as a case study, this research plans and designs the village’s overall pattern at three levels—point, line, and plane—while preserving its traditional internal texture, based on the spatial pattern of Baotou City. The design creates a spatial pattern of “one core, two wings, three axes, and multiple nodes”, enhancing the connectivity between the urban village and the surrounding urban blocks (Table 6);

(2) Implementing a skeletal network control system to improve urban transportation efficiency. In FUT-UVs, road accessibility, functional diversity, and functional mix are strongly correlated, while the correlation between plot ratio and road accessibility is moderate. This suggests that road accessibility alone is insufficient to support development, underscoring the need for a multi-tiered transportation network. The development of a three-dimensional, multi-level transportation network that integrates vehicle, public, and pedestrian traffic, will support diverse modes of transport, and improve overall traffic flow. This will enhance internal circulation and accessibility in FUT-UVs and strengthen their vitality by repairing, densifying, and streamlining the road network, measures address issues such as narrow village streets, dead-ends, and fragmented streets. Meanwhile, traffic management policies, such as speed limits for motor vehicles within FUT-UVs and standardized parking regulations, should be implemented to improve safety and traffic flow. An efficient transportation network will strengthen the connection between FUT-UV and surrounding areas, facilitating the flow of people, goods, and information, while boosting economic vitality and social development in the region.

5.2.2. Architectural Texture Stitching

(1) The development intensity of FUT-UV through construction and renovation will optimize the building layout, increase public space, and reduce building density. Based on the function of each area, the renovation or demolition of existing buildings should be evaluated and building density should be adjusted accordingly (Figure 12). Public spaces and buildings should be increased and linked to create an open, efficient, and interconnected spatial system within the complex. Increasing the number of floors in FUT-UVs can enhance construction intensity, boost functional facility density, optimize spatial structure, and improve space utilization. The interstitial and open spaces at the boundaries and within FUT-UVs can be utilized to create new public areas and activity venues, encouraging people to gather and move through these spaces, thereby stimulating urban vitality;

(2) The crafting of granular elements contributes to a distinctive urban spatial texture at the micro level. Elements like streetlights, flowerbeds, and road signs in FUT-UVs are designed to complement the village style, ensuring a cohesive and unified spatial environment. Reshaping micro-level elements will strengthen the cultural heritage and unique character of FUT-UVs, while enhancing residents’ sense of belonging and identity.

5.2.3. Functional Texture Stitching

(1) Enhancing and streamlining functional businesses. While FUT-UVs have a high functional diversity index, low-end businesses are concentrated and thrive within them. While preserving original industries, policies should promote the upgrading of business forms and functional diversification, complementing existing businesses and boosting urban vitality. The government can unlock an FUT-UV’s commercial potential by upgrading public service facilities while maximizing the preservation of historical buildings. Upgrading business functions has driven the transformation of the economic structure in FUT-UVs, boosting industry value and economic benefits;

(2) Increasing public leisure space. To reduce building density and increase porosity, the public leisure space is divided into centralized park green spaces that are convenient for large crowds to gather and pocket parks that are easily accessible. Expanding public leisure spaces will significantly improve the living environment for FUT-UV residents, enhancing their quality of life and sense of well-being;

(3) The design incorporates full-time functional mixing. Function mixing is carried out on different spatial and temporal scales. For example, policies can be implemented to strategically schedule functions like sports, leisure, dining, and mobile vendors to attract visitors at various times. Additionally, facilities for science, education, and culture could remain open throughout the day, ensuring a continuous flow of tourists. Continuous functional mixing will fully unlock urban space potential, improving land-use efficiency and boosting urban vitality.

5.3. Limitations of the Study

This study has some limitations. First, the limited amount of data may lead to certain errors in the analysis results. This study focused on typical urban villages and surrounding urban areas in Baotou City, using 400 valid sample units of 150 m × 150 m for analysis. The sample size is limited. While this does not impact the accuracy of the conclusions, it may affect the matching rate of various material elements. Second, the grid division affects the analysis of various material elements in the urban texture. A city is a complex system; in this study, the urban texture was analyzed through grid sampling. During the research process, changes in the position and scope of the grid sampling of the urban texture may have had a slight impact on the conclusions. Additionally, social and cultural factors influencing breaks in urban texture should be considered to further clarify the interaction between these areas and the surrounding urban environment. Therefore, conducting horizontal comparisons of FUT-UVs across different regions and further exploring the interaction between material and cultural factors will guide our future research.

6. Conclusions

This study sampled FUT-UVs and surrounding urban texture grids from the perspective of a multi-element overlay. It analyzed the texture characteristics and interaction mechanisms of FUT-UVs and surrounding urban areas, and accordingly put forward texture-splicing strategies conducive to the overall sustainable development of the city. The main conclusions are as follows:

(1) Compared with the surrounding urban areas, FUT-UVs exhibit the architectural characteristics of high-density and low-rise buildings (1–3 floors). The high building density and low porosity have led to a serious shortage of outdoor public spaces available for activities within FUT-UVs. The road networks within FUT-UVs are dense, but the roads are narrow, with low accessibility, and are isolated from the surrounding urban areas. The functional combination and diversity index are relatively low, and the urban vitality of enterprises is limited;

(2) Surrounding urban areas increase construction intensity by adding floors or increasing building density, while FUT-UVs mainly do so by raising floors. However, in FUT-UVs, there is a weak correlation between road accessibility and the floor area ratio or the average number of floors; areas with high road accessibility often have high building density. Through an overlapping correlation analysis with urban functional elements, it is evident that FUT-UVs concentrate low-end businesses within specific areas. While increasing building density enhances the functional mix and diversity to some extent, it does not notably improve functional density. Alternatively, increasing the average floor count and floor area ratio effectively boosts functional density. Road accessibility enhances vitality within FUT-UVs and can utilize highly accessible areas in surrounding urban areas to stimulate urban vitality;

(3) This paper proposes specific design strategies from the following three aspects: transportation; architecture; and functionality. It aims to redesign and reconstruct the spatial structure, traffic organization, as well as the functional and cultural framework of the region.

In conclusion, the main contribution of this study lies in the quantitative analysis of various physical elements of FUT-UVs and surrounding urban areas, objectively depicting the differences in the urban texture around FUT-UVs and the interaction mechanism between FUT-UVs and the surrounding urban areas. This study not only expands the perspectives and methods of urban research, but also optimizes the urban transportation network, improves the quality of urban space, and promotes the integration of urban functions, injecting new vitality into the sustainable development of cities.

Author Contributions

Conceptualization, W.W. and T.H.; methodology, W.W. and H.T.; software, H.T.; formal analysis, H.T.; investigation, H.T.; resources, H.T.; data curation, H.T.; writing—original draft preparation, H.T.; writing—review and editing, W.W. and H.T.; visualization, H.T.; supervision, W.W. and T.H. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Distribution map of FUT-UVs in central-western Baotou.

Figure 2. Location of Nanhao Village.

Figure 3. The research framework and processes of this study.

Figure 4. Diagram of graded-value partition matching method: (a) sample unit differentiation for material element A (numbers represent sample numbers); and (b) sample unit differentiation for material element B (numbers represent sample numbers).

Figure 5. Distribution of road elements and sample unit statistics: (a) distribution of road density in the urban village and surrounding urban areas; (b) statistics of different grade road density in the urban village and surrounding urban areas; (c) distribution of road accessibility in the urban village and surrounding urban areas; and (d) statistics of different grade road accessibility in the urban village and surrounding urban areas.

Figure 5. Distribution of road elements and sample unit statistics: (a) distribution of road density in the urban village and surrounding urban areas; (b) statistics of different grade road density in the urban village and surrounding urban areas; (c) distribution of road accessibility in the urban village and surrounding urban areas; and (d) statistics of different grade road accessibility in the urban village and surrounding urban areas.

Figure 6. Distribution of architectural elements and sample unit statistics: (a) distribution of the floor area ratio in the urban village and surrounding urban areas; (b) statistics of different grades of the floor area ratio in the urban village and surrounding urban areas; (c) distribution of the average number of floors in the urban village and surrounding urban areas; (d) statistics of the different grades of the average number of floors in the urban village and surrounding urban areas; (e) distribution of building density in the urban village and surrounding urban areas; and (f) statistics of different grades of building density in urban village and surrounding urban areas.

Figure 7. Distribution of functional facility elements and sample unit statistics: (a) distribution of functional density in urban village and surrounding urban areas; (b) statistics of different grades of functional density in urban village and surrounding urban areas; (c) distribution of the functional mix in the urban village and surrounding urban areas; (d) statistics of different grades of the functional mix in urban village and surrounding urban areas; (e) distribution of functional diversity index in the urban village and surrounding urban areas; and (f) statistics of different grades of the functional diversity index in the urban village and surrounding urban areas.

Figure 7. Distribution of functional facility elements and sample unit statistics: (a) distribution of functional density in urban village and surrounding urban areas; (b) statistics of different grades of functional density in urban village and surrounding urban areas; (c) distribution of the functional mix in the urban village and surrounding urban areas; (d) statistics of different grades of the functional mix in urban village and surrounding urban areas; (e) distribution of functional diversity index in the urban village and surrounding urban areas; and (f) statistics of different grades of the functional diversity index in the urban village and surrounding urban areas.

Figure 8. Kernel density distribution of different types of POI in Nanhao Village: (a) kernel density distribution of Sports and Recreation POI; (b) kernel density distribution of Medical Service POI; and (c) kernel density distribution of Science/Culture and Education Service POI.

Figure 9. Commercial and functional distribution map of Nanhao Village: (a) commercial distribution map of Nanhao Village; and (b) functional distribution map of Nanhao Village.

Figure 10. Analysis of grade matching between indicators of architectural and road elements.

Figure 11. Analysis of grade matching between indicators of architectural, road and functional facility elements.

Figure 12. Location and design diagram of newly constructed buildings in Nanhao Village.

Table 1

Fracture manifestations of FUT-UVs in Baotou.

Type	Features	Village Name	Illustration
Point-like FUT-UV	Small-scale with few single buildings and a simple structure, it has a negative but minimal impact on the surrounding urban area.	Dongya Village (Xinguang W Rd and Linyin M Rd, Baotou)	[Image omitted. Please see PDF.]
Linear FUT-UV	Affected by urban railways, highways, and rivers, these areas align linearly, exerting a greater impact on the city than point-like FUT-UVs.	Linnan Village (Minzu W Rd and Jian’an Ave, Baotou)	[Image omitted. Please see PDF.]
Areal FUT-UV	Consisting of one or more villages and multiple point-like FUT-UVs, the area is heavily impacted, leading to stagnation in the overall regional development.	The combined area of Nanpai, Nanshaliang, Beishaliang, and Bianqianghao Villages in Baotou City.	[Image omitted. Please see PDF.]

Table 2

FUT-UV indicator system and quantification standards.

Element	Indicator	Calculation Method	Calculation Formulas and Annotations
Road elements	Road density	The ratio of the total length of urban road centerlines to the area of the sample unit	${road}_{den}={\displaystyle \frac{L}{A}}$“L” represents the total length of urban road centerlines within the block, while “A” denotes the area of the block.
	Road accessibility	Utilizing Dijkstra’s algorithm to determine the shortest path and minimum resistance accessibility between two points	${road}_i={\displaystyle \frac{1}{n-1}}{\sum }_{\begin{array}{c}j=1\\ j\ne i\end{array}}^n\left(d_{ij}\right)$${road}_{acc}={\displaystyle \frac{1}{n}}{\sum }_{i=1}^n\left(A_i\right)$“roadi” denotes node “i”’s accessibility in the network, “roadacc” represents overall network accessibility, and “dij” is the minimum impedance between nodes “i” and “j”, measured in distance, time, or cost.
Architectural elements	Floor area ratio	The gross floor area to land area, is known as the construction intensity.	$FAR={\displaystyle \frac{Ar}{Al}}$“Ar” represents the total sum of all building areas within the block, while “Al” denotes the area of the block.
	Average number of floors	The average number of floors of all buildings within the sample unit	${building}_f={\displaystyle \frac{1}{n}}{\sum }_{n=1}^n{bf}_i$“i” denotes a building in the block, “bfi” is the number of floors in building “i”, and “n” is the total number of buildings.
	Building density	The ratio of building base area to sample unit area	${building}_{den}={\displaystyle \frac{1}{s}}{\sum }_{i=1}^n{m}_i$“i” represents a building in the block, “mi” denotes the base area of the i-th building, and “S” represents the block’s area.
Functional facility elements	Functional density	The ratio of the total number of POIs to the area of the sample unit.	${fun}_{den}={\displaystyle \frac{c_i}{s_i}}$$,(\mathrm{i}=\mathrm{1,2},3,\dots \dots ,n$)“Ci” represents the total number of POIs within a block, “Si” denotes the area of the block, and “n” is the total number of POI categories.
	Functional mix	Information entropy of all POI function types	${fun}_{mix}=-{\sum }_{i=1}^n\left(p_i\times \ln p_i\right)$$,(\mathrm{i}=\mathrm{1,2},3,\dots \dots ,n$)“i” represents a POI category, “pi” is the ratio of POIs in “i” to total POIs in a grid, and “n” is the total POI categories.
	Functional diversity index	Simpson’s index of each POI functional type	$FDI=1-{\sum }_{i=1}^n{\left({\displaystyle \frac{N_i}{N}}\right)}^2$“i” denotes the category of a specific functional POI, “Ni” represents the number of POIs in category “i”, and “N” is the total number of POIs within the grid.

Table 3

Grade-matching statistics of material elements.

Sample Unit	Material Element A Grade Assignment	Material Element B Grade Assignment	Grade Assignment Difference of |A − B|	Matching Result
1	3	4	1	Approximate matching
2	4	4	0	Precisely matching
3	4	3	1	Approximate matching
4	5	1	4	Mismatching
……

Note: The values of the sample units are classified into five grades based on natural breaks; each grade is assigned a value from 1 to 5 in ascending order.

Table 4

Statistics on grade-matching rate among various indicators of architectural and road elements.

Comparative Elements		Precisely Matching	Approximate Matching	All Area Sample Units Match Rate	Nanhao Village Area Sample Unit Matching Rate	Surrounding Urban Areas Sample Unit Matching Rate
FAR	buildingden	38.0%	42.5%	80.5%	20.0%	83.7%
buildingf	FAR	55.5%	38.0%	93.5%	100.0%	93.2%
	buildingden	29.8%	35.5%	65.3%	20.0%	67.6%
roadden	FAR	27.0%	44.0%	71.0%	50.0%	72.1%
	buildingf	21.3%	44.0%	65.3%	40.0%	66.6%
	buildingden	29.8%	44.0%	73.8%	85.0%	73.2%
roadacc	FAR	20.3%	35.0%	55.3%	40.0%	56.1%
	buildingf	16.3%	38.0%	54.3%	25.0%	55.8%
	Buildingden	27.8%	34.3%	62.0%	60.0%	62.1%
	roadden	21.5%	38.0%	59.5%	75.0%	58.7%

Table 5

Statistics on grade-matching rate among various indicators of architectural, road and functional facility elements.

Comparative Elements		Precisely Matching	Approximate Matching	All Area Sample Units Match Rate	Nanhao Village Area Sample Unit Matching Rate	Surrounding Urban Areas Sample Unit Matching Rate
funmix	funden	10.3%	19.5%	29.8%	20.0%	30.3%
FDI	funden	7.8%	20.5%	28.3%	20.0%	28.7%
	funmix	78.3%	21.8%	100.0%	100.0%	100.0%
buildingden	funden	30.5%	41.5%	72.0%	40.0%	73.7%
	funmix	16.5%	43.0%	59.5%	70.0%	58.9%
	FDI	16.3%	39.0%	55.3%	65.0%	54.7%
FAR	funden	41.8%	35.3%	77.0%	70.0%	77.4%
	funmix	12.0%	30.0%	42.0%	25.0%	42.9%
	FDI	9.3%	27.5%	36.8%	25.0%	37.4%
buildingf	funden	33.5%	33.0%	66.5%	70.0%	66.3%
	funmix	12.8%	30.5%	43.3%	15.0%	44.7%
	FDI	11.3%	25.3%	36.5%	10.0%	37.9%
roadden	funden	22.3%	37.3%	59.5%	70.0%	58.9%
	funmix	21.3%	35.0%	56.3%	50.0%	56.6%
	FDI	20.8%	31.3%	52.0%	50.0%	52.1%
roadacc	funden	16.5%	26.3%	42.8%	35.0%	43.2%
	funmix	21.8%	41.3%	63.0%	55.0%	63.4%
	FDI	19.0%	42.3%	61.3%	55.0%	61.6%

Table 6

Depiction of the spatial layout of ’One Core, Two Wings, Three Axes, and Multiple Nodes’.

Spatial Pattern	Spatial Name	Scene Depiction	Location Indication
One Core	The core of the Demonstration Area	The intersection point of the axis in Nanhao Village is a vibrant hub where a large number of pedestrians converge.	[Image omitted. Please see PDF.]
Two areas	Traditional Style Heritage Area	This region boasts traditional spatial texture, and rich historical resources.
	Modern Culture Innovation Area	This region boasts a dense population, high urban vitality, and strong residential-commercial character.
Three axises	Traffic Organization Axis	The original urban axis, Xinguang East Road, is extended into the fragmented urban texture.
	Functional Industrial Axis	The connection of the original regional axes in the northern, central, and southern sections of Nanhao Village.
	Greenscape Axis	Utilizing the central area of Nanhao Village, the green landscape spans the entire village.
Multiple nodes	The intersections between axes and between axes and major roads, as well as those with various regions of the village.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/buildings15010005/s1, Figure S1: Architectural Texture of Nanhao Village Area; Figure S2: Urban Form of Nanhao Village Area; Table S1: Statistics on Indicators of Various Elements for Sample Units in Nanhao Village Area; Table S2: Grade statistics for each sample unit in the Nanhao Village area; Table S3: Multi-factor Overlay Rating Difference Statistics.

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