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

Zhang, Yuqing; Shang, Kun; Shi, Zhipeng; Wang, Hui; Li, Xueming

doi:10.3390/land11010085

Cited by 9 publications

(3 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DMSP/OLS nighttime light images were divided Land 2024, 13, 840 4 of 26 into five different types of nighttime light areas in another study to explore the relationship between dynamic spatial expansion patterns and spatiotemporal characteristics [38]. Research utilizing nighttime light data to analyze urban vitality found that cities with high vitality usually boast convenient transportation and rich historical or cultural heritage [39]. However, most studies have relied on a single data source to identify the patterns of association between urban vitality and other urban characteristics.…”

Section: Explorations Of Urban Vitality Assisted By Multisource Datamentioning

confidence: 99%

Impacts of Built Environment on Urban Vitality in Cultural Districts: A Case Study of Haikou and Suzhou

Liu,

Li,

et al. 2024

Land

View full text Add to dashboard Cite

In the context of urban development, bridging the gap between urban regeneration and people’s demand for high-quality built environments is a current focus of research. Exploring the vitality of certain kinds of urban districts is imperative for comprehending human needs for specific built environments and fostering urban renaissance and advancement. This urgency arises from the prevailing lack of in-depth studies on district vitality, as current research primarily provides a general assessment of street vitality. Thus, this study aims to explore the correlations between indicators of urban vitality in cultural districts and built environments, using Haikou and Suzhou as case studies and employing multiple data sources (e.g., Baidu heat maps and nighttime light) and measurements. By applying a logit regression model, we find the following: (1) Traffic network integration has a positive impact on daytime vitality in Haikou and nighttime vitality in Suzhou, but it negatively affects nighttime vitality in Haikou. (2) In terms of nighttime vitality, both commercial density and greenery positively influence the overall blocks and various subgroups. (3) The proportion of cultural facilities in Suzhou has a detrimental effect on daytime vitality, especially for blocks with fewer permanent residents and lower land values. The present study, while limited to selected cultural blocks in Suzhou and Haikou, establishes the groundwork for a better comprehension of how spatial vitality can be enhanced at the street segment level, thereby contributing to the investigation of the varying impacts that built environment factors have on urban vitality in tourism cities at different stages of development. It uncovers the inherent latent characteristics found within cultural blocks across diverse regions and offers innovative perspectives and recommendations for optimizing the sustainable development of urban blocks.

show abstract

Section: Explorations Of Urban Vitality Assisted By Multisource Datamentioning

confidence: 99%

Impacts of Built Environment on Urban Vitality in Cultural Districts: A Case Study of Haikou and Suzhou

Liu,

Li,

et al. 2024

Land

View full text Add to dashboard Cite

show abstract

“…(3) City Economic Vibrancy Index Compared with artificial statistics, nighttime light data can directly capture the spatial distribution of artificial radiation in human settlements with less error [33]. It can be used to visualize the real-time state of economic activity and intensity of human activity [34], and is commonly used to assess urban economic activity [35]. This study uses nighttime light data to quantify urban economic vibrancy by preprocessing the month-by-month lighting data using operations to remove lighting outliers and derive the average pixel value within each grid (P h,t ).…”

Section: Urban Vibrancy Indicators (1) City Social Vibrancy Indexmentioning

confidence: 99%

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

Gong

Wang

et al. 2022

IJERPH

View full text Add to dashboard Cite

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.

show abstract

“…Although China's economy has begun to turn to connotative development, the construction of characteristic towns in different regions is still not ideal, and there exists a series of problems, including a lack of cultural support, insufficient benefit output, separation of life and production, and serious ecological destruction [5,6]. Some characteristic towns focus on their ecological maintenance and geographical development and pay too much attention to the external image, ignoring the development and integration of characteristic industries, which are not conducive to the sustainable development of the towns [7].…”

Section: Introductionmentioning

confidence: 99%

The Green and Adaptable Development Paths of Provincial Characteristic Towns in Taihu Lake Basin: A Synergy Perspective on Face Value and Resilience

et al. 2023

View full text Add to dashboard Cite

Enhancing the synergistic development level of face value and resilience is the key to achieving green and high-quality development of characteristic towns. This study takes 83 characteristic towns in Taihu Lake Basin as research samples, constructs a systematic evaluation index system of the face value and resilience, and scientifically classifies the face value and resilience of Taihu Lake Basin into high level, medium–high level, medium level, and low level, respectively, and explores the intrinsic influence mechanism of the deviation between the face value and resilience via the deviation index and synergy development degree model. The results show that (1) the face value of about 60% of the characteristic towns is above average, which is distributed in the northern and southeast regions of Taihu Lake Basin. In terms of the industry type, the face value level of characteristic towns of tourism, digital economy, information, and finance is high. (2) The number of characteristic towns with moderate resilience is the largest, accounting for 36.1%. Spatially, the characteristic towns with medium–high and high levels are mainly concentrated in Hangzhou, Kunshan, Wuxi, and Shanghai. In terms of the industry type, the resilience levels of tourism towns, digital economy towns, and modern service towns with distinctive industrial characteristics are higher. (3) The face value and resilience of most characteristic towns in Taihu Lake Basin are not synchronized, and 67.5% of the towns have a large deviation. We classify 83 characteristic towns into four categories: high robustness (Hj > 4.80), medium–high robustness (4.02 ≤ Hj ≥ 4.79), medium robustness (4.03 ≤ Hj ≥ 3.11), and low robustness (Hj < 3.10); the high robustness areas are concentrated in Suzhou–Wuxi–Changzhou and the northern part of Zhejiang. (4) We propose the differentiated development paths of synergistic development between face value and resilience, and the synergistic cooperation and governance mechanism of multiple subjects for the achievement of balanced development in characteristic towns. The conclusions of this study have important research value and practical significance for the sustainable development of similar characteristic towns.

show abstract

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

Cited by 9 publications

References 71 publications

Impacts of Built Environment on Urban Vitality in Cultural Districts: A Case Study of Haikou and Suzhou

Impacts of Built Environment on Urban Vitality in Cultural Districts: A Case Study of Haikou and Suzhou

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

The Green and Adaptable Development Paths of Provincial Characteristic Towns in Taihu Lake Basin: A Synergy Perspective on Face Value and Resilience

Contact Info

Product

Resources

About