Evaluating Urban Land Resource Carrying Capacity With Geographically Weighted Principal Component Analysis: A Case Study in Wuhan, China DOI
Binbin Lu,

Yilin Shi,

Sixian Qin

et al.

Transactions in GIS, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

ABSTRACT With the rapid urbanization in China, urban land resources gradually become core of development. This study spatially evaluated resource carrying capacity (LRCC) with a case built‐up area Wuhan from 2015 to 2020. Following an evaluation index system, five critical LRCC indicators, including population density, GDP per area, plot ratio, building and road network were selected by analytical hierarchical process. The synthesis however, is usually challengeable due homogeneous assumptions traditional techniques. In this study, we adopted local technique, geographically weighted principal component analysis, calculate comprehensive pressure (CCP) concerning varying contributions each indicator on their across different geographic locations. On mapping these spatial outputs Wuhan, highest CCP was found central areas, where size tends be influential dominant variable 62.69% subdistricts. Furthermore, increased construction over 5 years has led some peripheries 55.22% subdistricts show rising changes. GWPCA framework works well evaluating analyzing new perspective.

Language: Английский

Spatial-temporal correlation effects and persistent synergistic control benefits of fine particulate matter and carbon emissions in China DOI

Lihui Yan,

Chao He,

Jinmian Ni

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 124135 - 124135

Published: Jan. 17, 2025

Language: Английский

Citations

1
Geographical and temporal density regression DOI
Binbin Lu, Yigong Hu, Bo Huang

et al.

International Journal of Geographical Information Science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 22

Published: Feb. 17, 2025

Language: Английский

Citations

1
A local regression approach to studying single-person households and social isolation in the main Spanish cities: a new pathway of socio-spatial polarization? DOI Creative Commons
Federico Benassi, Ricardo Iglesias‐Pascual

Annals of Operations Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Abstract The growing number of people living alone in single-person households is a recent trend which reveals the incidence loneliness and social isolation. Loneliness has traditionally been associated with ageing, problems health well-being. However, voluntarily among young professional groups now on rise, possibly linked to individualism, narcissism and, spatially, new dimension socio-spatial segregation. This makes highly heterogeneous nowadays, lends greater importance their study. To address this issue, census tract analysis was conducted four largest Spanish cities examine characteristics households. study explored both global traits spatial local heterogeneity using Geographically Weighted Regression models. Our results show that, urban Spain, these types are closely presence immigrant population from EU, ageing working age, an inverse relationship income level at scale. relationship, together significant geographical concentration households, particular interest ehp us draw conclusions could facilitate planning dynamics analyzed. Finally, we reflect challenges that isolation poses context, analyzing its effects promoting public policies favor cohesion encounters.

Language: Английский

Citations

1
Evaluating Urban Land Resource Carrying Capacity With Geographically Weighted Principal Component Analysis: A Case Study in Wuhan, China DOI
Binbin Lu,

Yilin Shi,

Sixian Qin

et al.

Transactions in GIS, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

ABSTRACT With the rapid urbanization in China, urban land resources gradually become core of development. This study spatially evaluated resource carrying capacity (LRCC) with a case built‐up area Wuhan from 2015 to 2020. Following an evaluation index system, five critical LRCC indicators, including population density, GDP per area, plot ratio, building and road network were selected by analytical hierarchical process. The synthesis however, is usually challengeable due homogeneous assumptions traditional techniques. In this study, we adopted local technique, geographically weighted principal component analysis, calculate comprehensive pressure (CCP) concerning varying contributions each indicator on their across different geographic locations. On mapping these spatial outputs Wuhan, highest CCP was found central areas, where size tends be influential dominant variable 62.69% subdistricts. Furthermore, increased construction over 5 years has led some peripheries 55.22% subdistricts show rising changes. GWPCA framework works well evaluating analyzing new perspective.

Language: Английский

Citations

0