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Article

An Assessment of the Urban Streetscape Using Multiscale Data and Semantic Segmentation in Jinan Old City, China

by
Yabing Xu
1,*,
Hui Tong
1,
Jianjun Liu
1,
Yangyue Su
2 and
Menglin Li
1
1
School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China
2
School of Management Engineering, Shandong Jianzhu University, Jinan 250101, China
*
Author to whom correspondence should be addressed.
Buildings 2024, 14(9), 2687; https://doi.org/10.3390/buildings14092687
Submission received: 30 July 2024 / Revised: 21 August 2024 / Accepted: 26 August 2024 / Published: 28 August 2024
(This article belongs to the Special Issue Advances in Strategic Replanning and Reconstruction of Cultural Heritage)
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Abstract

:
Urban street space is a significant component of urban public spaces and an important aspect of people’s perceptions of a city. Jinan Old City exemplifies the balance between the supply of and demand for green spaces in urban streets. The sense of comfort and the demand level of street spaces are measured via the space demand index. Open platform data, such as those from Baidu Maps and Amap, are evaluated using methods including ArcGIS network analysis and Segnet semantic segmentation. The results obtained from such evaluations indicate that, in terms of the green space supply, the overall level for Shangxin Street in Jinan is not high. Only 24% of the selected sites have an adequate green space supply. The level on Wenhua West Road is higher than that on Shangxin Street. The block on the western side of Shangxin Street has the highest green space demand, with a decreasing trend from west to east. There are several higher selection points in the middle section of Shangxin Street. The demand is lowest in the middle of Wenhua East Road. Shangxin Street’s demand is higher than that of Wenhua West Road. The supply and demand are highly matched on Wenhua West Road and poorly matched on Shangxin Street, with 44.12% of the area in the “low supply, high demand” quadrant. This study proposes targeted optimization strategies based on supply and demand, thereby providing research ideas and methods for urban renewal.

1. Introduction

Jinan has been listed in the second batch of historical and cultural cities announced by the Chinese state. However, in regard to Jinan’s urban construction, some areas have experienced problems, such as being too negligent and having insufficient awareness of protection. This has resulted in the destruction or demolition of many original old streets, alleys, and buildings with rich historical connotations. While many old cities have lost their vitality during urban development, the remaining spatial forms still have enormous development potential. Their reconstruction plays an important role in the development of new urban elements in the surrounding areas. The cultural revival and spatial heritage reuse of old city blocks are closely related to the process of urban renewal. To date, extensive research on how to improve the quality of urban street space has been carried out by scholars at home and abroad, focusing on the following three aspects. The first is research on the evaluation of the quality of street space. Pei established a framework for the evaluation of the quality of street space in Dongcheng District, Beijing, from the perspectives of responsibility and legal rights, emphasizing the necessity of clarifying rights and responsibilities in the evaluation of the street space quality. Di compared the green space quality of different streets through a multidimensional and sub-index comprehensive evaluation framework for urban street space quality, providing scientific support for precise street space renewal design [1]. The second aspect is the analysis of the factors and mechanisms influencing the quality of street space. Representative studies are as follows. Long explored the contributing factors of green space quality in streets from a human perspective and evaluated the space quality based on the following two aspects: the level of street greening and the degree of urban image recognition [2,3,4]. The third aspect is the quantitative study of the balance between the supply and demand regarding the green space quality in streets. Representative studies are as follows. Wang suggested that the quantitative analysis of the supply and demand relationship in the green space quality of streets can better reflect the human–land relationship in the city, and that it is of great significance with respect to enhancing fairness and citizen well-being. Ye collected street view data on all streets in Shanghai Central City based on Baidu Street View, and used a machine learning algorithm to analyze the matching degree between the supply of street green space and its demand among the people, followed by identifying specific optimized streets. Cao constructed a quantitative measurement model with street view images and machine learning, providing reference methods for large-scale street green space evaluation [3,4,5,6].
In the existing research related to urban street space, the macro scale is often focused on, which makes it difficult to effectively match the spatial accuracy of the supply and demand relationship of the street green space quality at the urban medium–micro spatial scales. In smaller urban spaces, streets occupy an extremely important position, and their quality directly affects people’s daily travel experiences and the health level of the corresponding city. At the same time, the existing research on the representation of urban residents relies heavily on census data, which cannot meet the spatial granularity requirements in characterizing the distribution of residents. It also lacks systematic empirical analysis support in the classification of green visibility levels. In summary, in this study, we took Jinan Old City as the research area, simulated the supply of street green space by integrating multi-source data, and evaluated the quality of the street space. Targeted strategies to improve the quality of street space are proposed herein to offer support for urban construction from the perspective of supply–demand balance.

2. Materials and Methods

2.1. Study Area

The Shangxin Street historical block in Jinan contains various forms of historical buildings with abundant material, spiritual, and cultural resources that embody the heritage value of urban space. The renewal and development of the Shangxin Street historical block are of great significance in the protection of the historical and cultural heritage of Jinan. The formation of the Shangxin Street historical block can be traced back to the Qing Dynasty, which lasted from 1368 to 1904. Located in the southwestern corner of Weizihao, it reflects approximately 100 years of history. Shangxin Street is a bustling area with many thriving businesses and well-known mansions on par with Houzaimen Street in Mingfu City. According to the 1889 “Complete Map of Provincial Streets”, the relevant streets of the Shangxin historical block, such as Banbiaodian Street (now the northern section of Shangxin Street), Yingpan Street (which does not match the current location of Yingpan Street), and Yaowangmiao Street (now part of Luoyuan Street), were recorded among the earliest historical materials [4].
The development of Shangxin Street can be traced back to the early years of the Republic of China. Shangxin Street begins at Luoyuan Street in the north and connects to Wenhua West Road (the former site of Weiqiang) in the south, presenting gradually rising terrain from north to south, symbolizing a “rising step by step” pattern, and also the opening of a new road, hence the name Shangxin Street [5,6,7]. As one of the most intact old streets and alleys in Jinan, it has rich historical and cultural heritage.
Recently, with the completion of Qilu University, the Shangxin Street area has become a gathering place for celebrities and a model for modern urban construction and cultural prosperity in Jinan. It is also a place where artists, politicians, and new business elites can engage in research, creativity, and social activities [8,9,10,11].
The northern side of Shangxin Street retains significant historical features, including important historical buildings and typical residential buildings. The elevated bridge used to house the largest tea and flower market in Jinan’s old urban area. The eastern and western sides of the block on the southern side of Shangxin Street mainly contain modern public buildings, and the middle part consists mostly of multistory residential buildings built at the end of the last century [11]. On the eastern side of the multistory residential area is the famous Ethnic Street farmers’ market.

2.2. Characteristics of Block Space

The functional partition in a city includes commercial areas, residential areas, industrial areas, storage areas, cultural and educational areas, scenic areas, comprehensive areas, and development zones [12,13,14]. Shangxin Street is part of a residential historical block. It is mainly composed of low-rise and multistory residential buildings, with multiple schools, hospitals, and cultural attractions scattered throughout (see Figure 1).
According to their functions, the buildings of the block can be divided into low-rise residential buildings, educational buildings, commercial buildings, cultural buildings, office buildings, medical buildings, and multistory residential buildings (see Figure 2). The buildings on Shangxin Street are rich in functionality [15].
The southern block is surrounded by urban trunk roads, making transportation convenient. The northern block has more streets and pedestrian paths, making transportation inconvenient [16,17]. The northern area of Shangxin Street has the distinctive urban texture of the ancient city, with low-rise traditional residential buildings clustered in a courtyard style, while the southern block has a more modern residential texture, with multistory residential buildings distributed in a row (see Figure 3). Corresponding renovation strategies have been adopted for different urban texture characteristics.
The form of public space is closely related to the distribution of buildings. The public spaces on the northern side of the Shangxin Street area are narrow and scattered. They are not connected, but they are of interest due to their regional characteristics. The public space on the southern side mainly exists on stairs, and is relatively regular [18,19,20,21,22,23].
Shangxin Street’s historical block has a variety of historical buildings, including traditional residences, official buildings, commercial buildings, and religious buildings. These buildings have different characteristics in terms of their building classification, facade design, expropriation, additions, architectural form, floor plan layout, materials, and colors, as well as their structures and decorative features. The southern block is surrounded by urban trunk roads, making transportation convenient, while the northern block has more streets and pedestrian paths, making transportation inconvenient. In terms of the street and alley fabric, the buildings in the northern block are mainly distributed in traditional courtyards, while the buildings in the southern block are mainly distributed in a row of multistory residential buildings. In terms of the public space form, the northern block is relatively narrow and scattered, but has interesting and regional characteristics, while the southern block mainly exists on stairs with relatively regular forms. We can adopt different updating strategies according to the different textural features [24,25].

2.3. Research Methods

Recent advances in deep learning have shown that a fully convolutional network (FCN) can predict the semantic properties of each pixel in an image, which can then be used to produce natural object-level segmentation results. The FCN divides street view images into sub-scenes, each involving vehicles, roads, trees, or other items, with up to 151 natural objects (including an “unknown” category). The dimensions of the visual features are obtained by counting the number of pixels in each segmentation pool to produce an area ratio for each visual element in the image.

2.4. Research Framework

The framework of this research is as follows (see Figure 4). This study first analyzes the spatial quality and distribution characteristics of the Shangxin Street area. Based on the semantic segmentation analysis data of 172,000 street view images, we compare and analyze the changes in street space quality in the old city area using key indicators, such as the D/H and green visibility, and we analyze their spatial distribution characteristics. We then analyze the current situation regarding the spatial quality of the streets in the old city of Jinan and identify the human-scale problems of the streets in the old urban area at a micro level. We aim to provide guidance for the future development of Jinan and strategic support for the overall improvement of the quality of urban street space.

3. Results

3.1. Relatively Poor Functional Structure Density and Degree of Mixing

The main function of Shangxin Street’s historical block is residential, accounting for approximately 75% of the block, and it is mainly distributed over the north of Xujia Garden and on both sides of Yingpan Street. The office functions are mainly distributed on the northern side of Wenhua West Road. There is an educational facility inside the block at Shangxin Street Primary School. A large medical institution, Shandong University Qilu Hospital, is located 200 m southeast of the block. There are no other medical facilities inside the block. There are street restaurants along Luoyuan Street, located on the northern edge of Shangxin Street.
Deep learning data-based FCN visual image semantic segmentation tools are used to identify 150 material spatial elements, such as plants, buildings, roads, sky, and public facilities, in the street view data, to reclassify the material spatial elements, and to calculate the proportion of each type of element (see Figure 5).
The spatial green vision rate of the Qilu Hospital area is 14%, with a relatively low overall green vision rate. Only some streets and alleys have continuous greening, mainly consisting of tall roadside trees. The degree of openness is 6%. This low openness is mainly due to the canopies and building obstructions in some street and alley spaces, features that make the space varied and unoppressive. The enclosure degree is 56%, with a strong sense of spatial enclosure (see Figure 6). Some streets and alleys have a high street aspect ratio (D/H: the ratio of the street space width to the enclosed interface height), mainly due to the narrow width of the street and the alley space itself [26,27,28]. However, the buildings and street walls on both sides are high. An overly continuous interface can easily create a sense of blockage. The walkability of the street is 8%, which accounts for the lower proportion of the visual perception contributed by street and alley spaces compared to roads. Some streets and alleys lack sidewalks, and there is also the phenomenon of static traffic encroaching on pedestrian spaces. The proportion of pedestrian flow is only 1%, which is lower than the proportion of motor vehicles (6%). In instances of low pedestrian rights and streets mainly serving residential purposes, with few commercial activities, such as ground-level shops, the levels of pedestrian activities are also relatively low [29,30,31,32].

3.2. Unreasonable Spatial Organization

The single-center pattern has a weak correlation with public spaces and poor emergency response capabilities. In a substantial part of the residential historical block, public space is relatively scarce [33,34,35]. There are also phenomena such as disorderly parking, construction, and the occupation of space. The public space in the district is also prone to a single-center layout. This could easily lead to the district’s inability to operate in an orderly manner in emergencies.
In terms of spatial distribution, the public spaces in the Shangxin Street historical block are limited by the existence of different residential areas, and they lack a unified overall layout. The existing public spaces are mainly concentrated in modern residential areas and public buildings, such as theaters, which will be constructed later. However, due to the limited space, these public spaces lack connections with each other [36,37,38]. The result is severe fragmentation and an uneven distribution. This renders the area unable to provide a place for residents to engage in activities and communication, thereby affecting the balance of community emergency venues [39,40,41,42].
Shangxin Street’s historical block lacks outdoor activity spaces and the efficient utilization of activity venues. Therefore, residents are unable to engage in various outdoor activities, resulting in poor spatial vitality (see Figure 7).
The node spaces within the Shangxin Street historical block can be roughly divided into four types, as follows: the expansion type, the turning type, the setback type, and the enclosed type. The entrance positions of blocks along roads are mostly expansion nodes, such as the northern and southern ends of Shangxin Street. However, compared to the node space on the southern side, the entrance node space at the northern end is relatively narrow, and can only be used for short-term stays. This does not facilitate residents’ daily communication [43,44,45,46,47]. The turning nodes are often located at crossroads or T-junctions, and there can be safety hazards. Therefore, the frequency of use by residents is relatively low. The setback nodes are mainly distributed in the central areas of each street, and are the most suitable spaces for residents’ activities. However, due to the dense buildings and widespread illegal construction in the Shangxin Street area, there are very few setback nodes within the block. They are mainly concentrated on both sides of Yingpan Street, and most of the spaces are currently used for parking. Due to the large number of modern residential buildings in the block, mostly consisting of unit courtyards, enclosed nodes have been formed. However, these spaces are currently commonly used as parking spaces, or they have become cluttered areas with low space utilization.

3.3. Chaotic Street Network Organization and General Side Interface

Luoyuan Street and Wenhua West Road on both sides of the Shangxin Street historical block play important roles as the main roads of the city, bearing enormous traffic pressure. Shangxin Street, as a key thoroughfare connecting Luoyuan Street and Wenhua West Road, as well as an extension of Qingnian West Road to Luoyuan Street, attracts a large number of pedestrians and vehicles [48,49,50,51,52]. However, the narrowness of the road has rendered the traffic situation on Shangxin Street chaotic. The mix of pedestrians and vehicles is dangerous, and the other streets within the block are narrow and lack parking spaces. Therefore, many motorized and non-motorized vehicles have to park on the roadside, resulting in mixed street spaces that reduce the possibility for crossings. In terms of visual access, the streets and alleys on the Shangxin Street historical block are winding and varied. The small scale of the streets and alleys makes it difficult for pedestrians to have sufficient visual access. This can easily lead to visual interruptions and a lack of directional awareness. The design of the streets and alleys within the block also makes it difficult to create visual memories for pedestrians.
The number of streets and alleys within the historical block of Shangxin Street is relatively small in terms of connectivity, and the distribution of courtyards and residential buildings is mixed. The result is a winding and scattered pattern of streets and alleys within the block. There is also a serious phenomenon of private and disorderly construction by residents in the neighborhood, whereby the connections between the streets and alleys are gradually being replaced by walls. The result is shorter streets and paths, more interruption points, and a lack of interconnection, often causing dead ends [53,54,55,56,57].
The current situation of the side interface is generalized among the streets and alleys of Shangxin Street. The buildings on both sides of the northern areas of Shangxin Street are mostly single-story residential buildings with a relatively flat outline on the side interface (see Figure 8). Although the architectural style is unified, the disorderly facade destroys the traditional style and lacks a sense of hierarchy. Therefore, the contour of the side interface does not change significantly. The continuity of the scale, contour, and style is better, but the transparency is poor, and the spatial feeling is oppressive. The scattered roadside trees on both sides of Yingpan Street and Nanxin Street add a certain level of hierarchy to the side interface of the streets and alleys, but the contours are either too concave or too convex, resulting in poor continuity [58,59,60,61,62,63].

3.4. Relatively Poor Cultural Atmosphere

Field visits to the historical block of Shangxin Street showed that there are differences in the spatial and cultural atmosphere of the street. The cultural atmosphere around traditional residential buildings and cultural heritage units is relatively satisfactory, while the cultural atmosphere around modern residential areas is relatively poor. The scattered nature and poor quality of the cultural heritage units in the block negatively affect the entire block. Older people who have lived in the block for a long time have a deep emotional attachment to it. However, the other residents in the block have a weak sense of identification with Shangxin Street, and it is necessary to improve the spatial and cultural atmosphere of the block.
Today, the former Wanzihui site at the end of Shangxin Street has the richest cultural atmosphere within the block. However, the tall walls convey a sense of alienation and oppression. Places or buildings related to revolutionary activities within the block have gradually been forgotten, and their cultural atmosphere is being lost due to long-term disrepair or a lack of management. Most residents believe that there is a lack of cultural facilities within the block, making it impossible to provide venues for cultural construction activities. This results in a poor sense of belonging and identity among most residents of Shangxin Street.

3.5. Privatization of Public Spaces

In the 1970s, a rapid increase in the population in the block led to a housing shortage. Due to this, some residential buildings were constructed. During this period, the purpose of residential area construction was to meet the housing needs of the residents, and there was little consideration for the planning of the neighborhood, as well as historical and cultural factors. As a result, the phenomenon of mixing traditional residential buildings with modern residential areas emerged. In this process, the planning of public spaces was neglected. The subsequent rapid urban development meant that the original courtyard space in Shangxin Street’s historical block could no longer meet the needs of modern living. This situation led to the privatization and occupation of public spaces by the residents. The resulting phenomenon of unauthorized construction and disorderly addition is serious; hence, the internal fabric of the block has been altered, leading to gradual disorder and a sharp reduction in the areas dedicated to outdoor public activities [64,65,66,67].

3.6. Poor Emergency Response Capabilities

The dense population and lack of infrastructure and organizational management on Shangxin Street mean that the living environments and sanitary conditions experienced by the residents are poor. The increase in the building density within the block has also led to a significant reduction in public spaces. Problems such as disorderly construction, pipeline construction, parking, a lack of green spaces, and road occupation have seriously affected the capacity of public spaces, greatly reducing the emergency response capabilities. The chaotic street and alley networks, the privatization of public spaces, and the low emergency response capabilities described above all contribute to the inability of the public spaces to meet the residents’ current needs for living and recreation. These factors are important causes of maladjustment problems.
The emergency response capabilities of the public spaces are insufficient in the Shangxin Street historical block. This mainly arises from two factors. Firstly, the problem of residents occupying public spaces within the block is serious. Behaviors such as parking vehicles, occupying space, and building temporary structures without permission have led to a shortage of public space resources, and an inability to provide emergency shelters in the face of uncertain risks. Secondly, the quality of the existing public spaces is poor, or their capacity is limited. They cannot meet the basic usage needs and transformation requirements of the residents.
The emergency response capabilities of the public facilities are also insufficient. At present, the public facilities in the Shangxin Street historical block mainly include garbage bins, public toilets, parking spaces, and information signs. Other facilities are relatively lacking, and many facilities are old and insufficient in number.

4. Discussion

Based on the analysis of the semantic segmentation, spatial texture, and existing contradictions in the Shangxin Street historical block, the recommended renewal strategies for Shangxin Street are as follows.

4.1. Improving the Density and Degree of Mixing of the Functional Structure

More official and commercial functions should be created to enhance the diversity and vibrancy of the Shangxin Historic District. This would bring more activities and opportunities to the neighborhood, thereby creating a thriving community [68]. Planning and policy guidance would increase the construction of medical and other public service facilities to meet the basic needs of the residents. This would provide better healthcare and other public services to the community, thereby improving the quality of life and well-being of the residents.

4.2. Optimizing the Spatial Organization

The layout of the public spaces should be optimized, and the public activity spaces of the block should be increased to enhance the community interaction and vitality of the block. This would provide a platform for residents to communicate and interact, thereby promoting community cohesion and a sense of mutual identity. There have been successful cases of this in previous studies, such as that in Shenzhen [69,70,71]. The planning and construction of outdoor activity venues should also be strengthened, and more outdoor activity spaces should be created to increase the vitality and attractiveness of the neighborhood. This would attract more people to the neighborhood, who could participate in activities that could help the community to thrive.
The spatial nodes of the block should also be improved, and specific attention should be paid to the spaciousness and comfort of the entrance nodes. This would improve the convenience of residents’ daily interactions, allowing for more comfort and ease when entering and exiting the neighborhood. The optimized design of the entrance node would also create a welcoming atmosphere, thereby creating a better impression of the neighborhood. In turn, this would strengthen the residents’ sense of belonging and community. Moreover, it is important to avoid gentrification and internet celebrity transformation. The focus should be on meeting the needs of the residents in their daily lives, rather than on improving the spatial effect.

4.3. Optimizing the Organization of the Street Network

The aim, based on the existing street network, is to improve the traffic capacity and safety of the block. By optimizing the road layout and traffic planning, the traffic flow is facilitated, and traffic congestion is reduced. The length of the pedestrian sight passages should also be increased to address the twists and turns of the streets and alleys, and to provide better directionality and visual memory. This would make it easier for pedestrians to navigate the neighborhood, reduce their likelihood of becoming lost, and enhance the overall pedestrian experience. The local government in Amsterdam has put these strategies into practice, with good results [72].
The connections between the streets and alleys should also be strengthened, interruption points should be reduced, and dead ends should be avoided, thereby improving the connectivity of the neighborhoods. The travel distances between pedestrians and vehicles could be shortened by connecting the streets and alleys, thereby promoting the neighborhood’s mobility and interoperability. A large number of historic buildings in the Shangxin District are clustered together. If accessibility to this area could be improved, it would be easier for residents and visitors to reach their destinations. The use-value of these buildings would be greatly enhanced, thereby improving their conservation.

4.4. Strengthening the Cultural Atmosphere

Attention should be paid to the protection and restoration of the cultural heritage to enhance the cultural atmosphere of the block. The historical and cultural heritage of the block should be promoted by protecting the integrity and uniqueness of the historical buildings and cultural sites, and by offering rich cultural experiences to residents and visitors. The construction and activities of cultural facilities should be actively supported, and cultural exchanges and artistic exhibitions should take place. Venues suitable for hosting various cultural activities and art exhibitions should be provided, and the block should become a cultural center full of creativity and an artistic atmosphere. These cultural facilities could become places for people to communicate and interact, attracting the participation and attention of artists, cultural enthusiasts, and community residents.
Regular repairs and maintenance would ensure that these valuable elements of historical heritage remain in a good condition and contribute to the overall cultural atmosphere of the block. These historical and cultural buildings and sites could become unique symbols of the block, attracting interest and appreciation and adding charm and uniqueness to the block.

4.5. Enhancing the Emergency Capabilities

The capacity and quality of the public spaces should be extended to ensure the provision of emergency shelters in emergencies. Block planning and design should be carried out, taking into account the need to assemble and evacuate residents, and the need to provide safe and spacious areas, as well as appropriate emergency shelter facilities. The emergency response capabilities of the public facilities should be improved to ensure that the necessary support and services are provided in the event of disasters or emergencies. These measures have been implemented in Hong Kong, and have received positive feedback [73,74,75]. This could include implementing emergency rescue equipment, providing emergency medical services, and establishing emergency communication and contact centers [76]. The organization of public facilities should be reinforced, as should the development of emergency plans, ensuring timely responses and the provision of the necessary assistance.
Residents should be encouraged to actively participate in and support the maintenance and management of the public spaces. Public education and training should take place to enhance the emergency awareness and self-rescue abilities of the residents. Regular organized training activities should be provided to teach basic emergency knowledge and skills so that the residents are able to respond appropriately in emergencies.

5. Conclusions

This study analyzes the historical evolution, location, component elements, textural characteristics, current situation, and existing contradictions of the Shangxin Street historical and cultural block. It proposes strategies for the reuse of the block’s spatial heritage; these strategies aim to overcome the challenges faced by the current urban development and renewal, and provide feasible measures to promote the protection and renewal of historical and cultural districts. The buildings surrounding Shangxin Street are old. They have diverse spatial types and frequent changes in architectural appearance. At present, the historical buildings in the Shangxin Street area are mostly occupied by residents, and the building space has been severely damaged. Many courtyard houses have been divided into several small courtyards, and the phenomenon of unauthorized construction is prevalent. A micro update mode involving small-scale updates, replacements, and renovations could effectively resolve the contradiction between residents’ everyday activities and the maintenance of the historical architectural style. In summary, this study takes the Jinan Old City as the research area, simulates the supply of street green space by integrating multi-source data, and determines the matching relationship between the green space supply and demand, and evaluates the quality of the street space. Targeted strategies to improve the quality of the street space are proposed to offer support to urban construction from the perspective of supply–demand balance. This study has some limitations and requires further validation and testing.

Author Contributions

Conceptualization, Y.X. and H.T.; methodology, Y.X. and Y.S.; software, Y.X.; validation, Y.X., Y.S., and H.T.; formal analysis, Y.X. and H.T.; investigation, Y.X.; resources, Y.X. and J.L.; data curation, Y.X.; writing—original draft preparation, Y.X.; writing—review and editing, Y.X. and Y.S.; visualization, M.L.; supervision, Y.X.; project administration, Y.X. and J.L.; funding acquisition, Y.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Science Foundation of China (No. 72204149), the Key Research and Development Soft Science Program of Shandong Province (No. 2023RKY07018), the Key Project of Philosophy and Social Sciences in Jinan City (No. JNSK23B23), the Yabing Xu Doctoral Scholars Grant Program of Shandong Jianzhu University (No. X21109Z), the Natural Science Foundation of Shandong Province (No. ZR2021QE207), and the Youth Innovation Team Program for Higher Educational of Shandong Province of China (No. 2022KJ317).

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 that there are no competing interests.

References

  1. Araoz, G.F. Preserving heritage places under a new paradigm. J. Cult. Herit. Manag. Sustain. Dev. 2011, 1, 55–60. [Google Scholar] [CrossRef]
  2. Gao, S.; Chen, R. Protection and reconstruction: The witness of the birth of American industrial civilization—John H. Ceffey heishi river canyon National heritage corridor. J. Chongqing Univ. 2014, 37, 51. [Google Scholar]
  3. Douet, J. Industrial Heritage Retooled: The TICCIH Guide to Industrial Heritage Conservation; Routledge: New York, NY, USA, 2016. [Google Scholar]
  4. Wu, J.; Bai, Z. Spatial and temporal changes of the ecological footprint of China’s resource-based cities in the process of urbanization. Resour. Policy 2022, 75, 102491. [Google Scholar] [CrossRef]
  5. Tan, J.; Zhang, P.; Lo, K.; Li, J.; Liu, S. The urban transition performance of resource-based cities in Northeast China. Sustainability 2016, 8, 1022. [Google Scholar] [CrossRef]
  6. Macioszek, E.; Grana, A.; Krawiec, S. Identification of factors increasing the risk of pedestrian death in road accidents involving a pedestrian with a motor vehicle. Arch. Transp. 2023, 65, 7–25. [Google Scholar] [CrossRef]
  7. Mallach, A. Demolition and preservation in shrinking US industrial cities. Build. Res. Inf. 2011, 39, 380–394. [Google Scholar] [CrossRef]
  8. Curwell, S.; Deakin, M.; Cooper, I.; Paskaleva-Shapira, K.; Ravetz, J.; Babicki, D. Citizens’ expectations of information cities: Implications for urban planning and design. Build. Res. Inf. 2005, 33, 55–66. [Google Scholar] [CrossRef]
  9. Bitaraf, A.; Saeedeh Zarabadi, Z.S.; Zabihi, H. Rereading the criteria of vitality in historical places with emphasis on the approach of heritage tourism. Islam. Art. Stud. 2021, 18, 103–123. [Google Scholar]
  10. Alexander, C. The Timeless Way of Building; Oxford University Press: Paddyfield, UK, 1979. [Google Scholar]
  11. Jan, J.F. Application of open-source software in community heritage resources management. ISPRS Int. J. Geo Inf. 2018, 7, 426. [Google Scholar] [CrossRef]
  12. Wu, J.; Lu, Y.; Gao, H.; Wang, M. Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning. Comput. Environ. Urban. Syst. 2022, 91, 101716. [Google Scholar] [CrossRef]
  13. Wijesuriya, G. Living Heritage: A Summary; ICCROM: Rome, Italy, 2018; pp. 1–13. [Google Scholar]
  14. Labadi, S.; Logan, W. (Eds.) Approaches to Urban Heritage, Development and Sustainability. In Urban Heritage, Development and Sustainability, 1st ed.; Routledge: New York, NY, USA, 2015; pp. 1–20. [Google Scholar]
  15. Zhang, J. Conservation and Creation: Beijing Tsinghua Tongheng Planning and Design Institute Heritage Protection and Urban-Rural Development Research Center Album; Archicreation: Beijing, China, 2018. [Google Scholar]
  16. Landorf, C. Managing for sustainable tourism: A review of six cultural World Heritage Sites. J. Sustain. Tour. 2009, 17, 53–70. [Google Scholar] [CrossRef]
  17. Zhang, P.; Ghosh, D.; Park, S. Spatial measures and methods in sustainable urban morphology: A systematic review. Landsc. Urban. Plan. 2023, 237, 104776. [Google Scholar] [CrossRef]
  18. López, F.J.; Lerones, P.M.; Llamas, J.; Gómez-García-Bermejo, J.; Zalama, E. A review of heritage building information modeling (H-BIM). Multimodal Technol. Interact. 2018, 2, 21. [Google Scholar] [CrossRef]
  19. Schweber, L.; Leiringer, R. Beyond the technical: A snapshot of energy and buildings research. Build. Res. Inf. 2012, 40, 481–492. [Google Scholar] [CrossRef]
  20. Zhu, Y.; Maags, C. Heritage Politics in China: The Power of the Past; Routledge: London, UK, 2020. [Google Scholar]
  21. Ye, Y.; Li, B.; Wu, Y. Concepts of planning heritage and corresponding practices in the World. Urban. Plan. Int. 2022, 37, 6. [Google Scholar]
  22. Barrett, B. Roots for the National Heritage Area family tree. Georg. Wright Forum 2003, 20, 41–49. [Google Scholar]
  23. Li, W.; Yu, K.; Li, D. Heritage corridor and a primary theoretic framework on study of integ rated conservation of the great canal. Urban. Probl. 2004, 1, 28–31. [Google Scholar]
  24. He, Q.; Jiang, K.; Guo, D. A Researcfl on planning of corridor protection for the Beijing-Hangzhou grand canal in Hangzhou. China Anc. City 2010, 5, 40–45. [Google Scholar]
  25. Orbaşli, A. Is tourism governing conservation in historic towns? J. Archit. Conserv. 2000, 6, 7–19. [Google Scholar] [CrossRef]
  26. Zeayter, H.; Mansour, A.M.H. Heritage conservation ideologies analysis–Historic urban Landscape approach for a Mediterranean historic city case study. HBRC J. 2018, 14, 345–356. [Google Scholar] [CrossRef]
  27. Guo, M.; Sun, M.; Pan, D.; Wang, G.; Zhou, Y.; Yan, B.; Fu, Z. High-precision deformation analysis of Yingxian wooden pagoda based on UAV image and terrestrial LiDAR point cloud. Herit. Sci. 2023, 11, 1. [Google Scholar] [CrossRef]
  28. Zhao, X.; Marnane, K.; Greenop, K. The role of digital technologies in recording values of human settlements: Testing a practical Historic Urban Landscape approach in China and India. Digit. Creat. 2021, 32, 253–274. [Google Scholar] [CrossRef]
  29. Minervino Amodio, A.M.; Di Paola, G.; Rosskopf, C.M. Monitoring coastal vulnerability by using DEMs based on UAV spatial data. ISPRS Int. J. Geo Inf. 2022, 11, 155. [Google Scholar] [CrossRef]
  30. Chan, T.O.; Xiao, H.; Liu, L.; Sun, Y.; Chen, T.; Lang, W.; Li, M.H. A post-scan point cloud colorization method for cultural heritage documentation. ISPRS Int. J. Geo Inf. 2021, 10, 737. [Google Scholar] [CrossRef]
  31. Chen, J.; Pellegrini, P.; Ma, G. Identifying resettlement communities’ urban regeneration opportunity through GIS-based spatial analysis in Suzhou Metropolitan area. Urban Reg. Plan. 2021, 6, 146. [Google Scholar] [CrossRef]
  32. Yin, S.; Guo, X.; Jiang, J. Extracting the urban landscape features of the historic district from street view images based on deep learning: A case study in the Beijing Core area. ISPRS Int. J. Geo. Inf. 2022, 11, 326. [Google Scholar] [CrossRef]
  33. Lin, G.; Xiang, L.; Sang, K. Scenic railway mapping: An analysis of spatial patterns in France based on historical GIS. ISPRS Int. J. Geo. Inf. 2022, 11, 99. [Google Scholar] [CrossRef]
  34. Pepe, M.; Costantino, D.; Alfio, V.S.; Restuccia, A.G.; Papalino, N.M. Scan to BIM for the digital management and representation in 3D GIS environment of cultural heritage site. J. Cult. Herit. 2021, 50, 115–125. [Google Scholar] [CrossRef]
  35. Chen, J.; Tian, W.; Xu, K.; Pellegrini, P. Testing small-scale vitality measurement based on 5D model assessment with multi-source data: A resettlement community case in Suzhou. ISPRS Int. J. Geo Inf. 2022, 11, 626. [Google Scholar] [CrossRef]
  36. Chen, J.; Gan, W.; Liu, N.; Li, P.; Wang, H.; Zhao, X.; Yang, D. Community quality evaluation for socially sustainable regeneration: A study using multi-sourced geospatial data and AI-based image semantic segmentation. ISPRS Int. J. Geo Inf. 2024, 13, 167. [Google Scholar] [CrossRef]
  37. Zhao, M.; Liu, N.; Chen, J.; Wang, D.; Li, P.; Yang, D.; Zhou, P. Navigating post-COVID-19 social–spatial inequity: Unravelling the Nexus between community conditions, social perception, and spatial differentiation. Land 2024, 13, 563. [Google Scholar] [CrossRef]
  38. Ye, Y.; Zhang, L.; Yan, W.; Zeng, W. Measuning street greening quality from humanistic perspective: A large-scale analysis based on Baidu street view images and machine learning algorithms. Landsc. Archit. 2018, 25, 6. [Google Scholar]
  39. Xu, L.; Meng, R.; Chen, Z. Fascinating streets: The impact of building facades and green view. Landsc. Arch. 2017, 7, 27–33. [Google Scholar]
  40. Shi, C.; Yuan, Q.; Pan, H.; Ye, Y. Measuring Walkability of street space and its design control in the context of new analytical techniques:A case study of Shanghai Jing’an temple area. Shanghai Urban Plan. Rev. 2020, 9, 24–29. [Google Scholar]
  41. Saarman, E.; Gleason, M.; Ugoretz, J.; Airamé, S.; Carr, M.; Fox, E.; Frimodig, A.; Mason, T.; Vasques, J. The role of science in supporting marine protected area network planning and design in California. Ocean. Coast. Manag. 2013, 74, 45–56. [Google Scholar] [CrossRef]
  42. Nickerson, J.W.; Adams, O.; Attaran, A.; Hatcher-Roberts, J.; Tugwell, P. Monitoring the ability to deliver care in low- and middle-income countries: A systematic review of health facility assessment tools. Health Policy Plan 2015, 30, 675–686. [Google Scholar] [CrossRef]
  43. Bourdic, L.; Salat, S.; Nowacki, C. Assessing cities: A new system of cross-scale spatial indicators. Build. Res. Inf. 2012, 40, 592–605. [Google Scholar] [CrossRef]
  44. Liu, X.; He, J.; Yao, Y.; Zhang, J.; Liang, H.; Wang, H.; Hong, Y. Classifying urban land use by integrating remote sensing and social media data. Int. J. Geogr. Inf. Sci. 2017, 31, 1675–1696. [Google Scholar] [CrossRef]
  45. Scott, L.M.; Janikas, M.V. Spatial statistics in ArcGIS. In Handbook of Applied Spatial Analysis; Springer: Berlin/Heidelberg, Germany, 2010; pp. 27–41. [Google Scholar]
  46. Liu, B.; Wu, C.; Xu, W.; Shen, Y.; Tang, F. Emerging trends in GIS application on cultural heritage conservation: A review. Herit. Sci. 2024, 12, 139. [Google Scholar] [CrossRef]
  47. Huang, Y. Bibliometric analysis of GIS applications in heritage studies based on Web of Science from 1994 to 2023. Herit. Sci. 2024, 12, 57. [Google Scholar] [CrossRef]
  48. Chen, J.; Pellegrini, P.; Wang, H. Comparative residents’ satisfaction evaluation for socially sustainable regeneration—The case of two high-density communities in Suzhou. Land 2022, 11, 1483. [Google Scholar] [CrossRef]
  49. Chen, J.; Pellegrini, P.; Xu, Y.; Ma, G.; Wang, H.; An, Y.; Shi, Y.; Feng, X. Evaluating residents’ satisfaction before and after regeneration. The case of a high-density resettlement neighbourhood in Suzhou, China. Cogent Soc. Sci. 2022, 8, 2144137. [Google Scholar] [CrossRef]
  50. Long, Y.; Ye, Y. Human-scale urban form: Measurements, performances, and urban planning & design interventions. S. Archit. 2016, 36, 39–45. [Google Scholar]
  51. Jacobs, J. The Death and Life of Great American Cities; Random House: New York, NY, USA, 1961. [Google Scholar]
  52. Gehl, J. Livet Mellem Husene, Udeaktiviteter og Udemiljøer; Arkitektens Forlag: København, Denmark, 1996. [Google Scholar]
  53. Berghauser Pont, M.Y.; Haupt, P.A. Spacematrix. Space, Density and Urban Form; nai010 Publishers: Rotterdam, The Netherlands, 2010. [Google Scholar]
  54. De Nadai, M.; Staiano, J.; Larcher, R.; Sebe, N.; Quercia, D.; Lepri, B. The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective. In Proceedings of the 25th International Conference World Wide Web, Montréal, QC, Canada, 11–15 April 2016; pp. 413–423. [Google Scholar]
  55. Ewing, R.; Clemente, O.; Neckerman, K.M.; Purciel-Hill, M.; Quinn, J.W.; Rundle, A. Measuring Urban Design: Metrics for Livable Places; Island Press: Washington, DC, USA, 2013. [Google Scholar]
  56. Koo, B.W.; Guhathakurta, S.; Botchwey, N.; Hipp, A. Can good microscale pedestrian streetscapes enhance the benefits of macroscale accessible urban form? An automated audit approach using Google street view images. Landsc. Urban Plan 2023, 237, 104816. [Google Scholar] [CrossRef]
  57. Sivarajah, U.; Kamal, M.M.; Irani, Z.; Weerakkody, V. Critical analysis of Big Data challenges and analytical methods. J. Bus. Res. 2017, 70, 263–286. [Google Scholar] [CrossRef]
  58. Sulis, P.; Manley, E.; Zhong, C.; Batty, M. Using mobility data as proxy for measuring urban vitality. J. Spat. Inf. Sci. 2018, 16, 137–162. [Google Scholar] [CrossRef]
  59. Jin, X.; Long, Y.; Sun, W.; Lu, Y.; Yang, X.; Tang, J. Evaluating cities’ vitality and identifying ghost cities in China with emerging geographical data. Cities 2017, 63, 98. [Google Scholar] [CrossRef]
  60. Meng, Y.; Xing, H. Exploring the relationship between landscape characteristics and urban vibrancy: A case study using morphology and review data. Cities 2019, 95, 102389. [Google Scholar] [CrossRef]
  61. Ye, Y.; Zhuang, Y.; Zhang, L.; van Akkelies, N. Designing urban spatial vitality from morphological perspective–A study based on quantified urban morphology and activities’ testing. Urban Plan Int. 2016, 31, 26–33. [Google Scholar]
  62. Wang, N.; Wu, J.; Li, S.; Wang, H.; Peng, Z. Spatial features of urban vitality and the impact of built environment on them based on multi-source data: A case study of Shenzhen. Trop. Geogr. 2021, 41, 1280–1291. [Google Scholar]
  63. Ning, X. Impact Analysis of Land Use Structure and Urban Vitality; Shenzhen University: Shenzhen, China, 2016; p. 61. [Google Scholar]
  64. Huang, J.; Cui, Y.; Chang, H.; Obracht-Prondzyńska, H.; Kamrowska-Zaluska, D.; Li, L. A city is not a tree: A multi-city study on street network and urban life. Landsc.Urban Plan 2022, 226, 104469. [Google Scholar] [CrossRef]
  65. Huang, J.; Obracht-Prondzynska, H.; Kamrowska-Zaluska, D.; Sun, Y.; Li, L. The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland. Landsc. Urban Plan 2021, 206, 103977. [Google Scholar] [CrossRef]
  66. Huang, J.; Cui, Y.; Li, L.; Guo, M.; Ho, H.C.; Lu, Y.; Webster, C. Re-examining Jane Jacobs’ doctrine using new urban data in Hong Kong. Environ. Plan. B Urban Anal. City Sci. 2022, 50, 76–93. [Google Scholar] [CrossRef]
  67. Li, B. Research on accelerating the construction of ecological livable city. Chin. Econ. 2014, 24, 11–12. [Google Scholar]
  68. Liang, X.; Zhao, T.; Biljecki, F. Revealing spatio-temporal evolution of urban visual environments with street view imagery. Landsc. Urban Plan 2023, 237, 104802. [Google Scholar] [CrossRef]
  69. Liu, J.; Ettema, D.; Helbich, M. Street view environments are associated with the walking duration of pedestrians: The case of Amsterdam, the Netherlands. Landsc. Urban Plan 2023, 235, 104752. [Google Scholar] [CrossRef]
  70. Cooper, C.H.V.; Harvey, I.; Orford, S.; Chiaradia, A.J.F. Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows. Transportation 2021, 48, 643–672. [Google Scholar] [CrossRef]
  71. Cooper, C.H.V.; Chiaradia, A.J.F. sDNA: 3-D spatial network analysis for GIS, CAD, Command Line & Python. SoftwareX 2020, 12, 100525. [Google Scholar]
  72. GB 50180-2018; Residential Facilities Planning and Construction Control Requirements. China Urban Planning and Design Institute: Beijing, China, 2018; p. 43.
  73. Goetz, A.R.; Vowles, T.M.; Tierney, S. Bridging the qualitative–quantitative divide in transport geography. Prof. Geogr. 2009, 61, 323. [Google Scholar] [CrossRef]
  74. Jervis, M.G.; Drake, M.A. The use of qualitative research methods in quantitative science: A review. J. Sens. Stud. 2014, 29, 234–247. [Google Scholar] [CrossRef]
  75. Hollstein, B. Qualitative approaches. In The SAGE Handbook of Social Network Analysis; Sage Publications: Thousand Oaks, CA, USA, 2011; pp. 404–416. [Google Scholar]
  76. Singh, J. Environmental conservation of medieval Telč Heritage Castle, Czech Republic: Detailed explanation of the building management and environmental control philosophy required to preserve 14th-century structures. Build Res. Inf. 1994, 22, 222–227. [Google Scholar] [CrossRef]
Buildings 14 02687 g001
Figure 1. Overall functional distribution of the block.
Figure 1. Overall functional distribution of the block.
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Figure 2. Current distribution of building functions.
Figure 2. Current distribution of building functions.
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Figure 3. Street fabric: buildings’ distribution (source: author).
Figure 3. Street fabric: buildings’ distribution (source: author).
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Figure 4. Research framework (arrows are used to indicate the sequence of steps and the direction of the process).
Figure 4. Research framework (arrows are used to indicate the sequence of steps and the direction of the process).
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Figure 5. Images derived from semantic segmentation in Jinan Old City.
Figure 5. Images derived from semantic segmentation in Jinan Old City.
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Figure 6. Results of semantic segmentation in Jinan Old City.
Figure 6. Results of semantic segmentation in Jinan Old City.
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Figure 7. Analysis of depth divided by height (D/H).
Figure 7. Analysis of depth divided by height (D/H).
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Figure 8. Analysis of D/H in Jinan Old City.
Figure 8. Analysis of D/H in Jinan Old City.
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Xu, Y.; Tong, H.; Liu, J.; Su, Y.; Li, M. An Assessment of the Urban Streetscape Using Multiscale Data and Semantic Segmentation in Jinan Old City, China. Buildings 2024, 14, 2687. https://doi.org/10.3390/buildings14092687

AMA Style

Xu Y, Tong H, Liu J, Su Y, Li M. An Assessment of the Urban Streetscape Using Multiscale Data and Semantic Segmentation in Jinan Old City, China. Buildings. 2024; 14(9):2687. https://doi.org/10.3390/buildings14092687

Chicago/Turabian Style

Xu, Yabing, Hui Tong, Jianjun Liu, Yangyue Su, and Menglin Li. 2024. "An Assessment of the Urban Streetscape Using Multiscale Data and Semantic Segmentation in Jinan Old City, China" Buildings 14, no. 9: 2687. https://doi.org/10.3390/buildings14092687

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