Identification of Urban Renewal Potential Areas and Analysis of Influential Factors from the Perspective of Vitality Enhancement: A Case Study of Harbin City’s Core Area DOI Creative Commons
Xiquan Zhang,

Lizhu Du,

Xiaoyun Song

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1934 - 1934

Published: Nov. 17, 2024

In the context of people-centered and sustainable urban policies, identifying renewal potential based on vitality enhancement is crucial for regeneration efforts. This article collected population density data, house price built environment data to examine spatial pattern characteristics Harbin’s core area using autocorrelation analysis. Building these findings, a geographically weighted regression (GWR) model was constructed further analyze influencing mechanisms relevant factors. The analysis revealed significant development imbalances within area, characterized by differentiated uneven social economic between old city newly areas. Notably, in certain regions, construction intensity does not align with levels vitality, indicating opportunities renewal. Furthermore, examination key factors highlighted that accessibility commercial facilities had most substantial positive impact vitality. contrast, age distribution educational demonstrated strong correlation By clearly delineating specific areas potential, this study provided detailed characterization Harbin. Additionally, depicting local variations factors, it established analytical foundations objective references planning targeted locations. Ultimately, research contributes new insights frameworks analyses applicable other regions.

Language: Английский

Evaluating implied urban nature vitality in San Francisco: An interdisciplinary approach combining census data, street view images, and social media analysis DOI
Mingze Chen,

Yuxuan Cai,

Shuying Guo

et al.

Urban forestry & urban greening, Journal Year: 2024, Volume and Issue: 95, P. 128289 - 128289

Published: March 15, 2024

Language: Английский

Citations

19
Nonlinear and threshold effects of the built environment, road vehicles and air pollution on urban vitality DOI
Quang Cuong Doan, Jun Ma, Shuting Chen

et al.

Landscape and Urban Planning, Journal Year: 2024, Volume and Issue: 253, P. 105204 - 105204

Published: Sept. 19, 2024

Language: Английский

Citations

17
Investigating the relationship between built environment and urban vitality using big data DOI Creative Commons

Guifen Lyu,

Niwat Angkawisittpan, Xiaoli Fu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 2, 2025

Language: Английский

Citations

2
Residents’ seasonal behavior patterns and spatial preferences in public open spaces of severely cold regions: Evidence from Harbin, China DOI
Shuai Liang,

Hong Leng

Habitat International, Journal Year: 2025, Volume and Issue: 156, P. 103279 - 103279

Published: Jan. 7, 2025

Language: Английский

Citations

2
GWPCA-based spatial analysis of urban vitality: a comparative assessment of three high-altitude Himalayan towns in India DOI
Subham Roy, Suranjan Majumder, Arghadeep Bose

et al.

Journal of Spatial Science, Journal Year: 2023, Volume and Issue: 69(2), P. 593 - 620

Published: Oct. 18, 2023

ABSTRACTUrban vitality comprises the livingness, vibrancy and attractiveness of urban areas. This research analyzes in three Himalayan towns India: Darjeeling, Kalimpong, Kurseong. Using GWPCA method, 29 indicators across six domains were considered to develop a comprehensive index (UVI). The study also explores how growth design influence these towns. With help LISA Moran's I analyses, determines that town centers display high vitality. findings highlight role expansion patterns European-style blocks maintaining this vibrancy.KEYWORDS: Urban vitalityGWPCAurban expansionspatial analysisGIS AcknowledgmentsFirstly, authors would like express cordial thanks Department Geography Applied Geography, University North Bengal for providing opportunity conducting work. paper was completed during tenure UGC-JRF period. Furthermore, extend their sincere appreciation Editor-in-Chief Associate Editor invaluable comments suggestions. Lastly, are deeply grateful anonymous reviewers insightful remarks innovative ideas, which have substantially enriched content article.Disclosure statementNo potential conflict interest reported by author(s).Credit authorshipS.R. S.M. – Writing Original Draft, Conceptualisation, Formal analysis, Investigation, Methodology, Software, Visualisation, Review & Editing, Supervision. A.B. InvestigationI.R.C. Editing.Data availability statementThe data can be provided upon reasonable request from corresponding author.Informed consentAll co-authors read article before submission every step is informed all co-authors.

Language: Английский

Citations

34
Portraying business district vibrancy with mobile phone data and optimal parameters-based geographical detector model DOI
Feng Gao, Xingdong Deng,

Shunyi Liao

et al.

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 96, P. 104635 - 104635

Published: May 10, 2023

Language: Английский

Citations

31
Exploring the Relationship between Urban Vibrancy and Built Environment Using Multi-Source Data: Case Study in Munich DOI Creative Commons
Chao Gao, Shasha Li,

Maopeng Sun

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(6), P. 1107 - 1107

Published: March 21, 2024

Urbanization has profoundly reshaped the patterns and forms of modern urban landscapes. Understanding how transportation mobility are affected by spatial planning is vital. Urban vibrancy, as a crucial metric for monitoring development, contributes to data-driven sustainable growth. However, empirical studies on relationship between vibrancy built environment in European cities remain limited, lacking consensus contribution environment. This study employs Munich case study, utilizing night-time light, housing prices, social media, points interest (POIs), NDVI data measure various aspects while constructing comprehensive assessment framework. Firstly, distribution correlation types revealed. Concurrently, based 5Ds indicator system, multi-dimensional influence investigated. Subsequently, Geodetector model explores heterogeneity indicators along with its economic, social, cultural, environmental dimensions, elucidating their mechanism. The results show following: (1) exhibits pronounced uneven distribution, higher central western areas lower northern areas. High-vibrancy concentrated major roads metro lines located commercial educational centers. (2) Among multiple models, geographically weighted regression (GWR) demonstrates highest explanatory efficacy vibrancy. (3) Economic, significantly influenced environment, substantial positive effects from POI density, building road intersection mixed land use shows little impact. (4) Interactions among factors impact synergistic interactions population density generating effects. These findings provide valuable insights optimizing resource allocation functional layout Munich, emphasizing complex spatiotemporal offering guidance planning.

Language: Английский

Citations

14
Urban engineering insights: Spatiotemporal analysis of land surface temperature and land use in urban landscape DOI Creative Commons
Bo Shu, Yang Chen,

Kai-xiang Zhang

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 92, P. 273 - 282

Published: March 7, 2024

In the field of urban environment engineering, understanding relationship between land surface temperature (LST) and use cover (LULC) is essential in rapidly growing climatically unstable landscapes such as Chengdu. It helps alleviate magnitude intensity Urban Heat Islands (UHIs). Toward this aim, summer winter Landsat images were acquired four years from 1992 to 2021 used extract LULC classes, LST three indices Normalized Difference Vegetation Index (NDVI), Built-up (NDBI), Modified Water (MNDWI) analyze their spatiotemporal associations. Results showed that built-up areas expanded approximately six times (820.82 Km2, 584.96%) 2021. Meanwhile, mean increased both seasons, by 9.94 °C 0.95 winter. The LST-NDBI correlation was significant positive studied (0.437< r <0.874, p=0.00) while a very high variability observed LST-NDVI (-0.835< <0.255, LST-MNDWI (-0.632< <0.628, coefficients. According results, NDBI can be good intra- inter-annual predictor Chengdu, especially context its fast-paced physical expansion increasing UHI.

Language: Английский

Citations

13
Investigating the effects of urban morphology on vitality of community life circles using machine learning and geospatial approaches DOI
Sanwei He,

Zhen Zhang,

Shan Yu

et al.

Applied Geography, Journal Year: 2024, Volume and Issue: 167, P. 103287 - 103287

Published: May 13, 2024

Language: Английский

Citations

13
Multi-method analysis of urban green space accessibility: Influences of land use, greenery types, and individual characteristics factors DOI Creative Commons

K. Zhang,

Mingze Chen

Urban forestry & urban greening, Journal Year: 2024, Volume and Issue: 96, P. 128366 - 128366

Published: May 15, 2024

Urban green spaces (UGS) are an important foundation for supporting sustainable urban development and benefiting the well-being of residents. However, access to is a complex dynamic process. Existing studies have mainly used single method assess UGS accessibility, research on influencing factors has less focused multi-variable perspective. In this study, we innovatively integrated four methods—Container, Distance, Gravity, 2SFCA—to accessibility at LSOA level in Inner London. We examined impact land use patterns, space types, individual characteristics accessibility. Then, Spearman's correlation analysis Ordinary Least Squares (OLS) regression model were check relationship between multiple variables with The main findings as follows: (1) results based multi-method reflect variation distribution London, more than 80% LSOAs having below-average accessibility; (2) significantly influenced by factors, particularly race, income, education, crime, office, residential, non-park (multiple types beyond parks). This study highlights inequalities suggests strategies policymakers improve integration planning.

Language: Английский

Citations

13