Urban spatial structure in OECD cities: Is urban population decentralising or clustering?

Veneri, Paolo

doi:10.1111/pirs.12300

Cited by 54 publications

(37 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…North, Central, and South American countries may, in fact, exhibit differences in those relationships, and the model took such differences into account. Mexico, for example, is still undergoing a rapid urbanization process, and during the last decade it had the highest growth rate of urban population among OECD countries, as well as the largest decline of population outside functional urban areas (Veneri, 2015). …”

Section: Macroregional Differencesmentioning

confidence: 99%

Urban‐to‐rural Population Growth Linkages: Evidence From Oecd Tl3 Regions*

Veneri

Ruiz

2015

Journal of Regional Science

Self Cite

View full text Add to dashboard Cite

The objective of this paper is to understand, from an international comparative perspective, how population growth in rural regions is affected by the relationship with their nearby urban centers. By means of a cross-sectional analysis on OECD small regions (Territorial Level 3), the paper distinguishes spread effects-positive spillovers arising from urban growth-from the net effect of distance to nonrural places. The results show that spread effects outweigh backwash effects, so that rural regions benefit from growth in urban places. A rural region's distance from urban and intermediate regions has a negative effect on its population growth rate. Nevertheless, both the strength of this effect and the growth spillovers decline with distance, and this occurs relatively faster in Europe. The results further suggest that proximity to large urban areas has a higher positive influence than proximity to intermediate areas, but only outside Europe.

show abstract

Section: Macroregional Differencesmentioning

confidence: 99%

Urban‐to‐rural Population Growth Linkages: Evidence From Oecd Tl3 Regions*

Veneri

Ruiz

2015

Journal of Regional Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…The problematic part is that while maintaining economic development, it is very difficult to reduce additional land consumption [22]. In the OECD countries between 2001 and 2011, the trend of the decentralisation of population prevails in the analysis of mechanical population movements within functional urban areas, with population growth not taking place directly in existing cores but usually in their immediate vicinity, in places with low population densities [23], while such residents do not have to be from the core city, but also from other cities [24,25]. In addition, if there are more municipalities in the immediate background of the city, their spatial interaction in terms of expansion may occur within neighbouring municipalities, as individual municipalities are competing for new inhabitants, thus significantly promoting the growth of the core city [26].…”

Section: Suburbanisation In the Context Of Environmental Aspects And mentioning

confidence: 99%

Impact of Suburbanisation on Sustainable Development of Settlements in Suburban Spaces: Smart and New Solutions

2019

View full text Add to dashboard Cite

The aim of this article is to evaluate the impact of suburbanisation on the development of settlements with an emphasis on environmental aspects that need to be addressed in the process of extensive growth of municipalities in suburban regions. In the theoretical part, the article evaluates the processes of suburbanisation and their environmental impact. On a methodological level, municipalities in the suburban zone were first defined on the basis of driving distances. These municipalities were subjected to an analysis of the intensity of residential suburbanisation by calculating a multicriteria indicator from five selected criteria. In the second part of the analysis, a questionnaire survey of mayors was carried out in the particular municipalities. The responses were evaluated using the Likert scale method, and then statistically significant dependencies were sought among individual phenomena and environmental problems which need to be solved by the municipal management due to the growth of municipalities. It was found that the mayors consider changes in the landscape character to be among the most significant impacts of suburbanisation in the territory. A change in the rural character of municipalities because of the construction of urban-type houses is perceived as being very problematic. Another serious problem is the insufficient capacity of technical infrastructure such as sewerage and waste-water treatment. The costs of ensuring the quality of the environment and of public spaces, which are, in many cases, beyond the economic possibilities of municipalities, are also increasing significantly. The article also includes specifications of selected smart solutions and procedures that can help preserve the quality of the environment.

show abstract

“…The moving direction θ i,t is assumed to follow θ i,t~U (0, 2π). As in urban areas there usually exist one or more population centers (Veneri, 2017), we modify Kang and Han (2017) to take this into account. More specifically, to reproduce the negative-exponential pattern of population density identified in urban centers (Muth, 1967), we assume that participants have lower probabilities to move when they are closer to a population center, which is justifiable as people usually stay longer times in the working and entertainment places of the population center:…”

Section: Water Resources Researchmentioning

confidence: 99%

Reward‐Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent‐Based Model Simulation

Yang

Cai

2019

Water Resources Research

View full text Add to dashboard Cite

Crowdsourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowdsourcing management for rainfall monitoring. Specifically, we model the allocation of incentives (quantitatively measurable and limited rewards) among crowdsourcing participants for a theoretical rainfall monitoring case. For this purpose, we develop an integrated model comprising a reward allocation component to represent the decision‐making process of a central manager, an agent‐based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulate six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we find that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade‐off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward‐based participant management for crowdsourcing rainfall monitoring. The proposed crowdsourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as storm water management and water availability and biomass assessment for food and energy crops.

show abstract

Urban spatial structure in OECD cities: Is urban population decentralising or clustering?

Cited by 54 publications

References 54 publications

Urban‐to‐rural Population Growth Linkages: Evidence From Oecd Tl3 Regions*

Urban‐to‐rural Population Growth Linkages: Evidence From Oecd Tl3 Regions*

Impact of Suburbanisation on Sustainable Development of Settlements in Suburban Spaces: Smart and New Solutions

Reward‐Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent‐Based Model Simulation

Contact Info

Product

Resources

About