Farideddin Peiravian

Impact analysis of extreme events on flows in spatial networks

The objective of this study is to investigate the resilience of roads networks to extreme events using a GIS and network science approach. Using the specific case study of Chicago, three extreme event scenarios were simulated: (1) extreme flooding, (2) random zonal disturbance, and (3) central targeted disturbance. To measure their impacts and as a proxy for flows, we calculate and analyze how the betweenness centrality of each road segment is being redistributed in the network before and after each simulation. Moreover, by randomly selecting 100 nodes in the Chicago road system, we simulate 10,000 trips and examine how they are being affected by each extreme event scenario. Overall, we find that extreme events can have tremendous impacts. More importantly, different types of extreme events generate completely different impacts, and the notion of resilience therefore rapidly becomes sensitive to individual contexts, thus supporting the argument towards more scenario-based analyses.

Intersections of Jane Jacobs’ conditions for diversity and low-carbon urban systems: a look at four global cities

AbstractCountless cities are rapidly developing across the globe, pressing the need for clear urban-planning and design recommendations geared toward sustainability. This paper examines the intersections of Jane Jacobs’ four conditions for diversity with low-carbon and low-energy-use urban systems in four cities around the world: Lyon (France), Chicago (Illinois), Kolkata (India), and Singapore City (Singapore). After reviewing Jacobs’ four conditions for diversity, the four cities are introduced and their historical development context is described. A framework to study the cities along the following three dimensions is then presented: population and density, infrastructure development/use, and climate and landscape. These cities differ in many respects and their analysis is instructive for many other cities around the globe. Jacobs’ conditions are present in all of them, manifested in different ways and to varying degrees. Overall, the study results show that the adoption of Jacobs’ conditions seems to ...

Spatial data analysis of complex urban systems

Cities are complex systems that are constantly evolving to better allow people to connect with one another. Moreover, and similar to countless natural phenomena, cities exhibit inherent orders that can be captured and expressed through complex analyses of their components. Using a variety of large datasets, this work offers a ring-buffer approach to analyze the spatial characteristics of four components of Chicago urban system, namely: roads, intersections, buildings, and population+ employment. The complex nature of these four components manifests itself in power-law relationships, represented by their fractal dimensions. Results show that road length and number of intersections, and to a larger degree, population+employment count and building gross floor area exhibit significantly similar properties. The proposed method could further be used to analyze large demographic, socio-economic, and other geospatial datasets with the aim to study their impacts on relevant urban systems characteristics, including mobility, connectivity, and accessibility to name a few.