Towards Intelligence and Resilience: Creative Solutions for Further Urban Transition

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Urban Contexts and Urban-Rural Interactions".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1598

Special Issue Editors

School of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Interests: sustainable construction; building carbon emissions; community resilience
Special Issues, Collections and Topics in MDPI journals
Department of Building and Real Estate, Hong Kong Polytechnic University, Kowloon, Hong Kong
Interests: built environment; health and safety; resilient buildings; smart buildings; the elderly
Special Issues, Collections and Topics in MDPI journals
Department of Wood Science, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada
Interests: green building; building information modeling; life cycle assessment and building energy performance

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Guest Editor
Department of Applied Physics and Electronics, Umea University, 90187 Umea, Sweden
Interests: built environment; occupant behavior; extreme weather; climate and energy resilience

Special Issue Information

Dear Colleagues,

In the context of global climate change, uncertainty disturbance, aging infrastructure, and ineffective governance, cities are critical focal points for implementing strategies that promote intelligent, resilient, and inclusive growth. Innovative solutions are paramount to ensuring the future viability of both cities and residents.

We aim to explore the intersection of intelligence and resilience in urban transitions, including social, economic, and environmental dimensions, providing holistic approaches to complex urban challenges. Authors are encouraged to offer new insights into intelligent public service databases and platforms, urban infrastructure system planning, urban comprehensive energy system management, safe operation and resilience recovery of urban systems, urban public health event operations, and emergency decision-making.

This Special Issue aims to serve as a platform for advancing research and discussion on the critical need for innovative urban transition strategies in the face of global and local challenges. We welcome the submission of papers that address critical research questions in this field, use innovative methodologies and data sources, contribute to theoretical debates, or highlight fundamental patterns that deserve more attention. Topics of interest may include, but are not limited to, the following:

  • Multi-hazard risk coupling quantification methods;
  • Energy security mechanism under extreme events;
  • Organizational resilience of emergency commands and dispatch systems;
  • Material supply chain security and intelligent operation;
  • Health and safety resilience strategies for the urban environment;
  • Smart urban renewal towards achieving sustainability;
  • Cross-regional action plan for emergency responses.

Dr. Peng Cui
Dr. Fan Zhang
Dr. Haibo Feng
Dr. Kailun Feng
Guest Editors

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Keywords

  • multi-hazard risk coupling quantification methods
  • energy security mechanism under extreme events
  • organizational resilience of emergency commands and dispatch systems
  • material supply chain security and intelligent operation
  • health and safety resilience strategies for the urban environment
  • smart urban renewal towards achieving sustainability
  • cross-regional action plan for emergency responses

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Published Papers (2 papers)

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Research

23 pages, 6792 KiB  
Article
The Spatial–Temporal Evolution and Coupling of Population Distribution and Social Economy in the “Mid-Spine Belt of Beautiful China”
by Qiang Yang, Jinxin Yang, Wenkai Chen, Yutong Liang, Shaokun Jia and Yuanyuan Chen
Land 2025, 14(2), 235; https://doi.org/10.3390/land14020235 - 23 Jan 2025
Viewed by 338
Abstract
Population distribution and socioeconomic development are pivotal elements for achieving national sustainable development and represent critical aspects of the spatiotemporal heterogeneity and imbalance within the “Mid-Spine Belt of Beautiful China”. This study examines the spatial distribution patterns and evolutionary characteristics of the population [...] Read more.
Population distribution and socioeconomic development are pivotal elements for achieving national sustainable development and represent critical aspects of the spatiotemporal heterogeneity and imbalance within the “Mid-Spine Belt of Beautiful China”. This study examines the spatial distribution patterns and evolutionary characteristics of the population from 1935 to 2020 and economic dynamics from 2010 to 2020 in the “Mid-Spine Belt of Beautiful China” through methods such as spatial interpolation, spatial autocorrelation, and other advanced spatial analytical techniques. Furthermore, the article explores the coordination between population and economic development within this region by employing the gravity index and inconsistency index. The findings reveal that the population distribution in the “Mid-Spine Belt of Beautiful China” lacks significant aggregation characteristics, with pronounced spatiotemporal differentiation observed along the “Hu Line”. From 2010 to 2020, socioeconomic indicators exhibited substantial disparities in spatial agglomeration, characterized by marked heterogeneity. Regarding the coordination between population and economic dynamics, this study highlights a progressive reduction in the distance between the centers of population and economic gravity, accompanied by a declining deviation trend. This indicates an improvement in balance and an increase in the degree of coupling over time. Full article
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20 pages, 6380 KiB  
Article
A Comprehensive Study of Spatial Distribution, Pollution Risk Assessment, and Source Apportionment of Topsoil Heavy Metals and Arsenic
by Honghua Chen, Xinxin Sun, Longhui Sun, Yunce An, Ying Xiao, Jintao Zhang, Yunpeng Hong and Xiaodong Song
Land 2024, 13(12), 2151; https://doi.org/10.3390/land13122151 - 10 Dec 2024
Viewed by 813
Abstract
Accurately identifying pollution risks and sources is crucial for regional land resource management. This study takes a certain coastal county in eastern China as the object to explore the spatial distribution, pollution risk, and source apportionment of heavy metals in topsoil. A total [...] Read more.
Accurately identifying pollution risks and sources is crucial for regional land resource management. This study takes a certain coastal county in eastern China as the object to explore the spatial distribution, pollution risk, and source apportionment of heavy metals in topsoil. A total of 633 samples were collected from the topsoil with a depth ranging from 0 to 20 cm, which came from different topographical and land use types (e.g., farmland, industrial areas, and mining areas), and the concentrations of HMs and As were measured by using atomic fluorescence spectrometry and inductively coupled plasma mass spectrometry. Firstly, the spatial distribution of soil HMs (Cd, Cr, Hg, Ni, and Pb) and arsenic (As) was predicted by incorporating environmental variables strongly affecting soil formation into geostatistical methods and machine learning approaches. Then, various pollution indicators were employed to conduct pollution evaluations, and potential ecological risk assessments were implemented based on the generated soil map. Finally, source apportionment was conducted using random forest (RF), absolute principal component score–multiple linear regression (APCS-MLR), correlation analysis, and spatial distribution of soil HMs and As. Findings in this research reveal that the RF approach yielded the best spatial prediction performance (0.59 ≤ R2 ≤ 0.73). The Nemerow and geoaccumulation indices suggest that various pollution levels exist in this area. The average concentrations of As, Hg, and Ni are 7.233 mg/kg, 0.051 mg/kg, and 27.43 mg/kg respectively, being 1.14 times, 1.27 times, and 1.15 times higher than the background levels, respectively. The central–northern region presented a slight potential ecological risk, with Hg and Cd being identified as the primary risk factors. Natural, agricultural, transportation, and industrial and mining activities were identified as the main HMs and As sources. These findings will assist in the design of targeted policies to reduce the risks of HMs and As in urban soil and offer useful guidelines for soil pollution research in similar regions. Full article
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