Markus Schläpfer

• PhD
• Professor (Assistant) at Columbia University

The ability to understand and predict the flows of people in cities is crucial for the planning of transportation systems and other urban infrastructures. Deep-learning approaches are powerful since they can capture non-linear relations between geographic features and the resulting mobility flow from a given origin location to a destination locatio...

The ability to understand and predict the flows of people in cities is crucial for the planning of transportation systems and other urban infrastructures. Deep-learning approaches are powerful since they can capture non-linear relations between geographic features and the resulting mobility flow from a given origin location to a destination locatio...

The vehicle-to-grid (V2G) concept utilises electric vehicles as distributed energy storage and thus may help to balance out the intermittent availability of renewable energy sources such as photovoltaics. V2G is therefore considered to play an important role for achieving low-carbon energy and transportation systems in cities. However, the adequate...

Reliable and affordable access to electricity has become one of the basic needs for humans and is, as such, at the top of the development agenda. It contributes to socio-economic development by transforming the whole spectrum of people’s lives—food, education, healthcare. It spurs new economic opportunities, thus improving livelihoods. Using a comp...

Human mobility impacts many aspects of a city, from its spatial structure1,2,3 to its response to an epidemic4,5,6,7. It is also ultimately key to social interactions⁸, innovation9,10 and productivity¹¹. However, our quantitative understanding of the aggregate movements of individuals remains incomplete. Existing models—such as the gravity law12,13...

High quality census data are not always available in developing countries. Instead, mobile phone data are becoming a popular proxy to evaluate the density, activity and social characteristics of a population. They offer additional advantages: they are updated in real-time, include mobility information and record visitors’ activity. However, we show...

This is a reply to Martilli et al. (2020), Summer average urban-rural surface temperature differences do not indicate the need for urban heat reduction (https://doi.org/10.31219/osf.io/8gnbf).

A reliable and affordable access to electricity has become one of the basic needs for humans and is, as such, at the top of the development agenda. It contributes to socio-economic development by transforming the whole spectrum of people's lives - food, education, health care; it spurs new economic opportunities and thus improves livelihoods. Using...

Human mobility patterns are surprisingly structured. In spite of many hard to model factors, such as climate, culture, and socioeconomic opportunities, aggregate migration rates obey a universal, parameter-free, `radiation' model. Recent work has further shown that the detailed spectral decomposition of these flows -- defined as the number of indiv...

The interaction of all mobile species with their environment hinges on their movement patterns: the places they visit and how frequently they go there. In human society, where the prevalent form of cohabitation is in cities, the highly dynamic and diverse movement of people is fundamental to almost every aspect of socio-economic life, including soc...

Future land use/cover change (LUCC) analysis has been increasingly applied to spatial planning instruments in the last few years. Nevertheless, stakeholder participation in the land use modelling process and analysis is still low. This paper describes a methodology engaging stakeholders (from the land use planning, agriculture, and forest sectors)...

Urban heat islands (UHIs) exacerbate the risk of heat-related mortality associated with global climate change. The intensity of UHIs varies with population size and mean annual precipitation, but a unifying explanation for this variation is lacking, and there are no geographically targeted guidelines for heat mitigation. Here we analyse summertime...

High quality census data are not always available in developing countries. Instead, mobile phone data are becoming a go to proxy to evaluate population density, activity and social characteristics. They offer additional advantages for infrastructure planning such as being updated in real-time, including mobility information and recording temporary...

Collecting and analysing big data is beginning to change governance and societies worldwide. Not only is big data voluminous and complex in nature, but it also comes from a number of different sources, across different time frames and spatial scales. On the urban scale, we suggest that data-informed design, rather than data-driven design, is a bett...

As cities grow, certain neighborhoods experience a particularly high demand for housing, resulting in escalating rents. Despite far-reaching socioeconomic consequences, it remains difficult to predict when and where urban neighborhoods will face such changes. To tackle this challenge, we adapt the concept of ‘bioindicators’, borrowed from ecology,...

In recent years, electrical load forecasting has received continuous research efforts aiming to improve the short-term prediction accuracy of local energy demands. However, current methods are not able to take explicitly into account the dynamic spatial population distribution over the course of a day, which is particularly relevant in dense urban...

In this paper, we introduce the Visit Potential Model (VPM), an integrated model to evaluate public space characteristics. It is an initial attempt to model and predict the potential presence of people in public places (i.e. their Visit Potential); the presence and flux of people being the underlying driver of all public space. We achieved this by...

As cities grow, certain neighborhoods experience a particularly high demand for housing, resulting in escalating rents. Despite far-reaching socioeconomic consequences, it remains difficult to predict when and where urban neighborhoods will face such changes. To tackle this challenge, we adapt the concept of `bioindicators', borrowed from ecology,...

The shape of buildings plays a critical role in the energy efficiency, lifestyles, land use and infrastructure systems of cities. Thus, as most of the world's cities continue to grow and develop, understanding the interplay between the characteristics of urban environments and the built form of cities is essential to achieve local and global sustai...

While many large infrastructure networks, such as power, water, and natural gas systems, have similar physical properties governing flows, these systems tend to have distinctly different sizes and topological structures. This paper seeks to understand how these different size-scales and topological features can emerge from relatively simple design...

Identifying changes in the spatial structure of cities is a prerequisite for the development and validation of adequate planning strategies. Nevertheless, current methods of measurement are becoming ever more challenged by the highly diverse and intertwined ways of how people actually make use of urban space. Here, we propose a new quantitative mea...

Detailed knowledge of the energy needs at relatively high spatial and temporal resolution is crucial for the electricity infrastructure planning of a region. However, such information is typically limited by the scarcity of data on human activities, in particular in developing countries where electrification of rural areas is sought. The analysis o...

While the size of cities is known to play a fundamental role in social and economic life, its impact on the structure of the underlying social networks is not well understood. Here, by mapping society-wide communication networks to the urban areas of two European countries, we show that both the number of social contacts and the total communication...

Dynamical processes on complex networks such as information exchange, innovation diffusion, cascades in financial networks or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree-degree correlations. Here, we introduce the concept of copulas in order to generate random networks with an arbi...

While degree correlations are known to play a crucial role for spreading phenomena in networks, their impact on the propagation speed has hardly been understood. Here we investigate a tunable spreading model on scale-free networks and show that the propagation becomes slow in positively (negatively) correlated networks if nodes with a high connecti...

The ongoing evolution of the electric power systems brings about the need to cope with increasingly complex interactions of technical components and relevant actors. In order to integrate a more comprehensive spectrum of different aspects into a probabilistic reliability assessment and to include time-dependent effects, this paper proposes an objec...

Increasing shares of fluctuating renewable energy sources induce higher and higher power flow variability at the transmission level. The question arises as to what extent existing networks can absorb additional fluctuating power injection without exceeding thermal limits. At the same time, the resulting power flow characteristics call for revisitin...

Dynamical processes on complex networks such as information propagation, innovation diffusion, cascading failures or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree-degree correlations. Here, we introduce the concept of copulas in order to artificially generate random networks with an...

Historically, both transmission and operational planning studies and criteria were for the most part deterministic. In today’s new market paradigm of separated generation, transmission and distribution entities most electric utilities still employ these traditional deterministic approaches for planning studies. As a result of the new market paradig...

The Pearson correlation coefficient is commonly used for quantifying the global level of degree-degree association in complex networks. Here, we use a probabilistic representation of the underlying network structure for assessing the applicability of different association measures to heavy-tailed degree distributions. Theoretical arguments together...

We study the splitting of regular square lattices subject to stochastic intermittent flows. Various flow patterns are produced by different groupings of the nodes, based on their random alternation between two possible states. The resulting flows on the lattices decrease with the number of groups according to a power law. By Monte Carlo simulations...

Different dynamical processes on complex networks such as epidemic spreading, information propagation or cascading phenomena are highly affected by the underlying topologies as characterized by, for instance, the degree-degree association. Here, we introduce the concept of copulas in order to artificially generate random networks with a rich \texti...

A framework for the analysis of the vulnerability of critical infrastructures has been proposed by some of the authors. The framework basically consists of two successive stages: (i) a screening analysis for identifying the parts of the critical infrastructure most relevant with respect to its vulnerability and (ii) a detailed modeling of the opera...

The simultaneous unavailability of several technical components within large-scale engineering systems can lead to high stress, rendering them prone to cascading events. In order to gain qualitative insights into the failure propagation mechanisms resulting from independent outages, we adopt a minimalistic model representing the components and thei...

We demonstrate that a broad spectrum of spreading processes taking place on complex networks can be categorized into two fundamentally different regimes, in which either positive or negative degree-degree correlation decelerates their propagation. This result can be explained by the role of the nodes with a high connectivity and their distribution...

Wide-area breakdowns of infrastructure networks often result from an initial, relatively slow system degradation that eventually evolves into a fast and uncontrollable failure propagation sequence, as has been observed on cascading line outages within electric power grids. In order to study the global dynamics of such failure processes in complex n...