Allometric scaling of countries

Zhang, Jiang; Yu, Tongkui

doi:10.1016/j.physa.2010.06.059

Cited by 33 publications

(30 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to our road length regression models, total road length in a country is strongly and positively related to its total land surface area, human population density, gross domestic product and OECD membership (table 1; figure 5). The variation explained by the regression models ranged from 63% for the local roads to 90% for all road types combined ( figure 5), which is larger than existing country-level regression models [28,29,49]. The positive relationships of road length with GDP, OECD membership and population density reflects that road densities are higher in developed countries with higher GDP, like those in Northwest Europe, as well as more densely populated countries like India, Bangladesh and Rwanda ( figure 3; figure 4).…”

Section: Global Patterns In Road Density and Qualitymentioning

confidence: 74%

“…Apart from the vector dataset, we also compiled gridded layers for road length (km of road per cell) and road density (meters of road per km 2 land area per cell) on a 5 × 5 arcminute resolution (approximately 8 × 8 km at the equator). In order to quantify possible relationships between road construction and socio-economic drivers, we then performed a multiple linear regression analysis where we related the total road length per country, as retrieved from the GRIP dataset, to four explanatory variables: the countries' total land surface area, human population density, gross domestic product per capita (GDP; in international PPP US$) and OECD membership (yes or no) [28,29]. Thus, we cover both human population and affluence, which are generally considered two main ultimate drivers of environmental impact [30].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Global patterns of current and future road infrastructure

Meijer

Huijbregts

Schotten

et al. 2018

Environ. Res. Lett.

494

303

View full text Add to dashboard Cite

Georeferenced information on road infrastructure is essential for spatial planning, socio-economic assessments and environmental impact analyses. Yet current global road maps are typically outdated or characterized by spatial bias in coverage. In the Global Roads Inventory Project we gathered, harmonized and integrated nearly 60 geospatial datasets on road infrastructure into a global roads dataset. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets. We then related total road length per country to country area, population density, GDP and OECD membership, resulting in a regression model with adjusted R 2 of 0.90, and found that that the highest road densities are associated with densely populated and wealthier countries. Applying our regression model to future population densities and GDP estimates from the Shared Socioeconomic Pathway (SSP) scenarios, we obtained a tentative estimate of 3.0-4.7 million km additional road length for the year 2050. Large increases in road length were projected for developing nations in some of the world's last remaining wilderness areas, such as the Amazon, the Congo basin and New Guinea. This highlights the need for accurate spatial road datasets to underpin strategic spatial planning in order to reduce the impacts of roads in remaining pristine ecosystems.

show abstract

Section: Global Patterns In Road Density and Qualitymentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Global patterns of current and future road infrastructure

Meijer

Huijbregts

Schotten

et al. 2018

Environ. Res. Lett.

494

303

View full text Add to dashboard Cite

show abstract

“…Although our study is based on human online activities, this quantitative relationship is not necessarily confined to an online context. The model may also be used to explain accelerating growth patterns in off-line social systems such as cities [9] and countries [12,13].…”

Section: Discussionmentioning

confidence: 99%

Accelerating growth and size-dependent distribution of human online activities

Zhang

2011

Phys. Rev. E

Self Cite

View full text Add to dashboard Cite

Research on human online activities usually assumes that total activity T increases linearly with active population P , that is, T ∝ P γ (γ = 1). However, we find examples of systems where total activity grows faster than active population. Our study shows that the power law relationship T ∝ P γ (γ > 1) is in fact ubiquitous in online activities such as micro-blogging, news voting and photo tagging. We call the pattern "accelerating growth" and find it relates to a type of distribution that changes with system size. We show both analytically and empirically how the growth rate γ associates with a scaling parameter b in the size-dependent distribution. As most previous studies explain accelerating growth by power law distribution, the model of size-dependent distribution is novel and worth further exploration.

show abstract

“…In contrast, the allometric scaling investigated on different scales, such as the ones among countries or provinces, yield divergent conclusions. For instance, it has been found that population increases sub-linearly with area while GDP increases linearly with population for countries (Zhang and Yu, 2010).…”

Section: Introductionmentioning

confidence: 99%

Allometric scaling, size distribution and pattern formation of natural cities

Li¹,

Wang²,

Zhang³

et al. 2015

Palgrave Commun

Self Cite

View full text Add to dashboard Cite

There has been a strong interest in more cogent definitions on economies of scale to reveal general urban growth laws and to develop urban performance metrics. Unstructured data, including satellite images, will provide us with new sources to do so by defining cities as aggregates of human activities. Such a uniform definition on the basis of nighttime light clusters is more consistent and economically meaningful than administrative or official boundaries. In comparison with patterns of city systems found in traditional census data, we examined the allometric scaling, size distribution and fractal geometry of natural cities. It can be concluded from our empirical analysis on regional, country and continental scales that a super-linear scaling between lightness and area with a stable exponent across different low light threshold levels generally holds for natural cities. But Zipf 's Law does not always apply over the whole range of lightness thresholds. Furthermore, we build a model based on the simple geometric matching mechanism to reproduce the self-organized formation process of nighttime light patterns. The statistical properties including allometries, size distributions and fractal geometries generated by our model are in good agreement with empirical evidence. These findings have profound implications for understanding the effects of simple aggregation behaviour in primitive stages of city formation and the urbanization process.

show abstract

Allometric scaling of countries

Cited by 33 publications

References 29 publications

Global patterns of current and future road infrastructure

Global patterns of current and future road infrastructure

Accelerating growth and size-dependent distribution of human online activities

Allometric scaling, size distribution and pattern formation of natural cities

Contact Info

Product

Resources

About