Suchergebnisse

Scientific collaboration, in most cases, is seen a joint action on a global scale that involves researchers from not just one region or one country but instead forming an international network of researchers. This type of epistemic communities build up especially in the case of analytical modes of knowledge production. Rationales for a global science system are needs for complementary ressources in an increasingly specialized world. Further, information and communication technologies contributed to flatten the world for intense, yet spatially distant collaboration. Based on the large scale analysis of the production of scientific publications in six distinct technologies/scientific fields from 2004 to 2008 these notions may be challenged. The probability of a collaboration is a power-law function of the distance between the participating authors: The higher the spatial proximity, the higher the chance of a jointly written paper, i.e. collaboration. Two main universal effects can be isolated: an intra-country effect following a power law with a negative exponent, and an inter-country effect that shows features of a random distributed distance function. The former effect outcompetes the latter by a factor of around 50-100. This behaviour has inevitable consequences for the design of research collaboration programs by governments world-wide.

We propose an upgraded gravitational model which provides population counts beyond the binary (urban/non-urban) city simulations. Numerically studying the model output, we find that the radial population density gradients follow power-laws where the exponent is related to the preset gravity exponent γ. Similarly, the urban fraction decays exponentially, again determined by γ. The population density gradient can be related to radial fractality and it turns out that the typical exponents imply that cities are basically zero-dimensional. Increasing the gravity exponent leads to extreme compactness and the loss of radial symmetry. We study the shape of the major central cluster by means of another three fractal dimensions and find that overall its fractality is dominated by the size and the influence of γ is minor. The fundamental allometry, between population and area of the major central cluster, is related to the gravity exponent but restricted to the case of higher densities in large cities. We argue that cities are shaped by power-law proximity. We complement the numerical analysis by economics arguments employing travel costs as well as housing rent determined by supply and demand. Our work contributes to the understanding of gravitational effects, radial gradients, and urban morphology. The model allows to generate and investigate city structures under laboratory conditions.

To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing…

The distribution of city populations has attracted much attention, in part because it constrains models of local growth. However, there is no consensus on the distribution below the very upper tail, because available data need to rely on "legal" rather than "economic" definitions for medium and small cities. To remedy this difficulty, we construct cities "from the bottom up" by clustering populated areas obtained from high-resolution data. We find that Zipf 's law for population holds for cities as small as 5,000 inhabitants in Great Britain and 12,000 inhabitants in the US. We also find a Zipf 's law for areas. JEL: R11, R12, R23

• Past and projected changes in sea level. IPCC AR5 2015 Sea-level rise a robust impact from climate change. Potentially disruptive High economic costs • Consequences mostly visible at the settlement level. Concentration of economic assets Coastal urbanization • Impacts for cities available but heterogeneous. Differences in data, methods & focus Coarse spatial data Comparability hindered • High resolution datasets and fast processing ; The research leading to these results has received funding from the European Union FP7/2007-2013 under grant agreement n° 607418.

To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing…

Abstract. Most climate change impacts manifest in the form of natural hazards. Damage assessment typically relies on damage functions that translate the magnitude of extreme events to a quantifiable damage. In practice, the availability of damage functions is limited due to a lack of data sources and a lack of understanding of damage processes. The study of the characteristics of damage functions for different hazards could strengthen the theoretical foundation of damage functions and support their development and validation. Accordingly, we investigate analogies of damage functions for coastal flooding and for wind storms and identify a unified approach. This approach has general applicability for granular portfolios and may also be applied, for example, to heat-related mortality. Moreover, the unification enables the transfer of methodology between hazards and a consistent treatment of uncertainty. This is demonstrated by a sensitivity analysis on the basis of two simple case studies (for coastal flood and storm damage). The analysis reveals the relevance of the various uncertainty sources at varying hazard magnitude and on both the microscale and the macroscale level. Main findings are the dominance of uncertainty from the hazard magnitude and the persistent behaviour of intrinsic uncertainties on both scale levels. Our results shed light on the general role of uncertainties and provide useful insight for the application of the unified approach.

Abstract
City systems are characterized by the functional organization of cities on a regional or country scale. While there is a relatively good empirical and theoretical understanding of city size distributions, insights about their spatial organization remain on a conceptual level. Here, we analyze empirically the correlations between the sizes of cities (in terms of area) across long distances. Therefore, we (i) define city clusters, (ii) obtain the neighborhood network from Voronoi cells, and (iii) apply a fluctuation analysis along all shortest paths. We find that most European countries exhibit long-range correlations but in several cases these are anti-correlations. In an analogous way, we study a model inspired by Central Places Theory and find that it leads to positive long-range correlations, unless there is strong additional spatial disorder—contrary to intuition. We conclude that the interactions between cities extend over large distances reaching the country scale. Our findings have policy relevance as urban development or decline can affect cities at a considerable distance.

Urban growth can take different forms, such as infill, expansion and leapfrog development. Here we focus on leapfrogging, which is characterised as new urban development bypassing vacant land. Analysing a sample of 100 global locations, we study the probability that land cover is converted from non-urban to urban as a function of the minimum distance to existing urban cells. The probability decreases with the distance but in many of the considered real-world samples it increases again just before the maximum possible distance. Comparing these empirical findings with numerical ones from a gravitational model, we discover that the characteristic increase can be found in both. Our results indicate that the conversion probability as a function of the distance to urban land cover includes three urban growth domains. (i) Expansion of existing settlements, (ii) discontinuous development of coincidental new settlements rather close to existing ones and (iii) leapfrogging of new settlements far away from existing ones. We conclude that gravitational effects can explain discontinuous development but leapfrogging can be attributed to a scarcity of developable land at long distances to settlements.

Even though people in our contemporary technological society are depending on communication, our understanding of the underlying laws of human communicational behavior continues to be poorly understood. Here we investigate the communication patterns in 2 social Internet communities in search of statistical laws in human interaction activity. This research reveals that human communication networks dynamically follow scaling laws that may also explain the observed trends in economic growth. Specifically, we identify a generalized version of Gibrat's law of social activity expressed as a scaling law between the fluctuations in the number of messages sent by members and their level of activity. Gibrat's law has been essential in understanding economic growth patterns, yet without an underlying general principle for its origin. We attribute this scaling law to long-term correlation patterns in human activity, which surprisingly span from days to the entire period of the available data of more than 1 year. Further, we provide a mathematical framework that relates the generalized version of Gibrat's law to the long-term correlated dynamics, which suggests that the same underlying mechanism could be the source of Gibrat's law in economics, ranging from large firms, research and development expenditures, gross domestic product of countries, to city population growth. These findings are also of importance for designing communication networks and for the understanding of the dynamics of social systems in which communication plays a role, such as economic markets and political systems.