Street space quality assessment refers to the extraction and appropriate evaluation of the space quality information of urban streets, which is usually employed to improve the quality of urban planning and management. Compared to traditional approaches relying on expert knowledge, the advances of big data collection and analysis technologies provide an alternative for assessing street space more precisely. With street view imagery (SVI), points of interest (POI) and comment data from social media, this study evaluates street space quality from the perspective of exploring and discussing the relationship among street vitality, service facilities and built environment. Firstly, a transfer-learning-based framework is employed for SVI semantic segmentation to quantify the street built environment. Then, we use POI data to identify different urban functions that streets serve, and comment data are utilized to investigate urban vitality composition and integrate it with different urban functions associated with streets. Finally, a function-driven street space quality assessment approach is established. To examine its applicability and performance, the proposed method is experimented with data from part area in Xiamen, China. The output is compared to results based on expert opinion using the correlation analysis method. Results show that the proposed assessment approach designed in this study is in accordance with the validation data, with the overall R2 value being greater than 0.6. In particular, the proposed method shows better performance in scenic land and mixed functional streets with R2 value being greater than 0.8. This method is expected to be an efficient tool for discovering problems and optimizing urban planning and management.

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Assessing Street Space Quality Using Street View Imagery and Function-Driven Method: The Case of Xiamen, China

Nighttime light images are valuable indicators of regional economic development, and nighttime light data are now widely used in town monitoring and evaluation studies. Using the nighttime light data acquired through Luojia1-01 and the geographic information system spatial analysis method, this study analyzed the spatial vitality pattern of 402 characteristic towns in six geographic divisions of China. The average DN (Digital Number) value of Guzhen, having the highest vitality level, was 0.05665221, whereas that of Xin’an, having the lowest vitality level, was 0.00000186. A total of 89.5% of towns have a low level of vitality. The regional differences were significant; high vitality towns are concentrated in economically developed coastal areas, mainly in two large regions of east China and south central. The average lighting densities of the towns in east China and south central were 0.004838 and 0.003190, respectively. The lighting density of the towns in west central was low, and the vitality intensity was generally low. A spatially significant positive correlation of small-town vitality was observed, and “high–high” agglomeration was primarily distributed in the Yangtze River Delta, Pearl River Delta, and Fujian coastal areas in east and south China. The towns with high vitality intensity had similarities in their geographical location, convenient transportation conditions, and profound historical heritage or cultural accumulation along with many industrial enterprises. This research empirically demonstrates the feasibility of using the 130-m-high resolution of the nighttime lighting data of Luojia1-01 to evaluate the vitality at the town scale, and the vitality evaluation focuses on the spatial attributes of the town, which is meaningful to guide the development of the town in each region given the vast area of China and the large differences in the development of different regions.

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Spatial Pattern of the Vitality of Chinese Characteristic Towns: A Perspective from Nighttime Lights

This paper focuses on the issue of vitality in urban public spaces, streets in particular, as a major indicator of their success and as one of the determinants of liveable cities. The study first provides a theoretical framework for understanding the social value and role of urban public
spaces in quality of urban life. Second, it discusses essential components of vitality in streets. Finally, it investigates vitality and its determinants in two main streets in Famagusta and Kyrenia, in North Cyprus. The paper
highlights some issues such as proper connection and proximity to important magnets, along with physical and social attributes in the street area.

Interrogating vitality of the streets in two cypriot towns / Siavash Jalaladdini and Derya Oktay

The development of tourism in historical villages has a certain impact on the native environment, which leads to visitors occupying community public spaces relatively frequently. The design of rural public spaces, especially in relation to the street network’s spatial configuration, significantly affects how villagers interact with one another. This research investigated the influence of street network space on the regional social interaction preferences of rural community populations by applying space syntax theory. Three typical villages in southern Anhui, China, were the subject of an observation analysis of social behaviors and pedestrian volumes on street networks. Using a segment model, it was possible to determine seven spatial configuration attributes of streets, including depth to the village entrance (DtoE), connectivity, curvature, the normalized angle choice (NACH) and integration (NAIN) with two radii. A considerable joint effect of street spatial type and spatial layout attributes on the regional social interaction preferences of rural community populations was found by MANOVA and stepwise regression analysis. The sampled community tends to engage in social activities in branch streets, and the pedestrian volume contained 67.1% of all the observed people in the street networks. Streets’ spatial attributes with lower NACH or NAIN levels (less usability or accessibility) and higher DtoE or curvature levels (more privacy or deformation) have greater influences on community pedestrian volumes. Regarding street type, the in-between space was found to have the most significant effect on the pedestrian volume of the branch streets, which are the preferred zones of community populations in the context of social activities.

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Understanding Social Spaces in Tourist Villages through Space Syntax Analysis: Cases of Villages in Huizhou, China

Quantitative assessment of urban vibrancy is crucial to understanding urban development and promoting sustainability, especially for rapidly developing areas and regions that have experienced post-disaster reconstruction. Taking Dujiangyan City, the hardest-hit area of the earthquake, as an example, this paper quantifies the urban economic, social, and cultural vibrancy after reconstruction by the use of multi-source data, and conducts a geographic visualization analysis. The purpose is to establish an evaluation framework for the relationship between the urban built environment elements and vibrancy in different dimensions, to evaluate the benefits of post-disaster restoration and reconstruction. The results show that the urban vibrancy reflected by classified big data can not be completely matched due to the difference in the data generation and collection process. The Criteria Importance Though Inter-criteria Correlation and entropy (CRITIC-entropy) method is used to construct a comprehensive model is a better representation of the urban vibrancy spatial characteristics. On a global scale, comprehensive vibrancy demonstrates high continuity and a bi-center structure. In the old town, the distribution of various urban vibrancies show diffusion characteristics, while those in the new district demonstrated a high degree of aggregation, and the comprehensive vibrancy is less sensitive to land-use mixture and more sensitive to residential land.

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How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment

In the context of China’s recent urbanization, the agglomeration and diffusion of the strip-city spatial network are gradually being reconstructed. The ways in which the street network structure affects the underlying logic of economic and social development is worthy of in-depth consideration. This study takes Lanzhou (a typical strip city in China) as a case study, using dynamic, geographic, big data and spatial syntactic-theory models to explore the influence of street network accessibility and structure on the spatial and temporal distribution of strip-city spatial vitality. We use Hotspot Analysis (Getis-Ord Gi*) to analyze the dispersal characteristics of street space vitality. In addition, the spatial and temporal heterogeneity characteristics and mechanism of the influence of street accessibility on spatial vitality are evaluated using the spatial Durbin model (SDM). The results show that: the temporal and spatial performance of urban vitality on weekdays and weekends conforms to people’s daily activities, offering similar spatial agglomeration and dispersion effects; accessibility and pedestrian-friendly streets have better urban spatial vitality clustering; street network integration significantly affects the reshaping of urban vitality, but there is apparent temporal heterogeneity in the degree of impact.

The Influence of Strip-City Street Network Structure on Spatial Vitality: Case Studies in Lanzhou, China

By describing the meanings and characteristics of emergency logistics and integrated transport, as well as the relationship between the two, a multi-objective, multi-stage mathematical optimization model based on “scenario-response” mode is proposed in this article. When factors such as time, cost and accident rate are taken into account, the optimization of integrated transport at different stages of public emergencies can be solved and analyzed using the improved Dijstra algorithm. The results show that this algorithm avoids the limitations of traditional multi-objective optimization methods, and can effectively resolve the multi-objective and multi-stage integrated transport in the optimization of emergency logistics effectively.

Junwei Zeng

Papers

The Influence of Strip-City Street Network Structure on Spatial Vitality: Case Studies in Lanzhou, China

Study on the Construction of Emergency Logistics and Integrated Transport System Based on "Scenario-Response" Mode