POI VizNet: New QGIS Tool to construct Visibility Networks in Cities

Network science and graph theory offer attractive models to describe urban phenomena and examine cases of urban planning and design. However, none of the existing network analysis tools consider simultaneously human visual perception and locations of urban activities. In this paper we introduce POI VizNet, a new QGIS plug-in that constructs various graphs of unobstructed lines of sight. The plug-in integrates an increasing amount of available GIS-based data of point of interest (POI) and visibility into one readily accessible analytical framework. Graphs are created between two types of decision points during urban travelstreet intersections and POIs, origins, and destinations of travel, by connecting these potential observer's decision locations in an open space between buildings. Therefore, the created graphs illustrate hypothetical visual trajectories of a person looking for a particular POI in the city. The graph is termed Integrative Visibility Graph (IVG) as it incorporates both navigational and functional aspects of the city (Figure 1a ). IVG examines connectivity of the particular location, i.e., predefined POI within the street network. In addition to IVG, the current version of the toolbox offers two separate modules of analysis corresponding to two additional types of visibility: Street Network Visibility Graph (SNVG) -creates visual connections between decision points of the street network, i.e., street intersections (Figure 1b ), and Point of Interest Visibility Graph (POIVG) -creates visual connections between POI that are visible from each other in a given building arrangement (Figure 1c ). In addition, POI VizNet provides advanced options to build graphs using a predefined viewing distance and perceptual perspective. Visibility graphs are constructed and visualised as new layers in QGIS and delivered as network files suitable for further exploration, analysis, and visualisation in various network software packages.

Small urban watercourses, often neglected and underdeveloped, have the potential to become integrated parts of the network of urban open public spaces. In this process, urban design plays the key role in their functioning and resilience, strengthening their capacity as high-quality open spaces. The current principles and roles of urban design only partially meet the requirements in making these spaces resilient. This article questions the existing principles and roles of the current practice and proposes a different perspective on the urban design of open public spaces surrounding small urban watercourses, within a framework of socio-ecological resilience. The research consisted of two parts. In the first part, based on both the specific characteristics of the public open spaces surrounding small urban watercourses and discussions of their quality, framed by the concept of socio-ecological resilience, a set of attributes was developed that defined their quality. In the second part, this set was tested through a case study of the Kumodraz stream in Belgrade, Serbia and translated into responsive urban design guidelines in a specific context. This was supported by a pilot survey of 346 potential users of the location. The findings of the case study show that urban design occupies a redefined and very specific position in the revitalization process of open public spaces surrounding small urban watercourses. In addition to its fundamental role in increasing the capacity of spaces and creating high-quality open spaces, it also helps to establish an integrated approach to the revitalization of the spaces surrounding small urban watercourses in a local context.

Long-voyage route planning method based on multi-scale visibility graph for autonomous ships

Measuring the Complexity of Urban Form and Design

Complex systems have become a popular lens for analyzing cities and complexity theory has many implications for urban performance and resilience. This paper develops a typology of measures and indicators for assessing the physical complexity of the built environment at the scale of urban design. It extends quantitative measures from city planning, network science, ecosystems studies, fractal geometry, statistical physics, and information theory to the analysis of urban form and qualitative human experience. Metrics at multiple scales are scattered throughout diverse bodies of literature and have useful applications in analyzing the adaptive complexity that both evolves and results from local design processes. In turn, they enable urban designers to assess resilience, adaptability, connectedness, and livability with an advanced toolkit. The typology developed here applies to empirical research of various neighborhood types and design standards. It includes temporal, visual, spatial, scaling, and connectivity measures of the urban form. Today, prominent urban design movements openly embrace complexity but must move beyond inspiration and metaphor to formalize what "complexity" is and how we can use it to assess both the world as-is as well as proposals for how it could be instead.

International Exhibitions (Expos) have long been recognised as dynamic laboratories for architectural and urban design innovation. While the iconic structures and transformative urban strategies of Expos have been extensively studied, the critical role of public open spaces within these global events has received comparatively little attention. This paper contends that Expo open spaces are far more than backdrops for architectural showcases; they are integral to the Expo experience, crucial for managing visitor flow, serving as hubs for social interaction, and experimental platforms for pioneering urban design concepts. Moreover, these spaces often leave a more enduring legacy on host cities than the temporary pavilions themselves. A historical review of Expos through the specific lens of open space design demonstrates how these spaces often have mirrored and shaped broader trends in urban public space design. This study highlights Expo open spaces’ profound and lasting influence on developing urban design principles and practices worldwide by examining their dual role as reflections of contemporary urban ideals and catalysts for innovative urban models.

Territories -in- between

Network science and graph theory are two important branches of mathematics and computer science. Many problems in engineering and physics are modeled with networks and graphs. Topological analysis of networks enable researchers to analyse networks in relation some physical and engineering properties without conducting expensive experimental studies. Topological indices are numerical descriptors which defined by using degree, distance and eigen-value notions in any graph. Most of the topological indices are defined as by using classical degree concept in graph theory, network and computer science. Recently two novel degree parameters have been defined in graph theory: Vertex-edge degree and Edge-vertex degree. Vertex-edge degree and edge-vertex degree based topological indices have been defined as parallel to their corresponding classical degree counterparts. Generalized Sierpinski networks have an important place of applications in view of engineering science especially in computer science. Classical degree based topological properties of generalized Sierpinski graphs have been investigated by many studies. In this article, vertex-edge degree based topological indices values of generalized Sierpinski graphs have been computed.

The complex, interconnected structure and function of ecological systems is apparent in their countless direct and indirect pathways of energy (e.g., a food web), mass (e.g., a movement corridor), and information (e.g., a social network). This Ignite ESA Session united multiple fields of ecology through the lens of a single, rapidly evolving, analytical framework: network analysis. This session examined basic and applied ecological problems in both naturally formed and anthropogenically altered networks of interactions. In particular, diverse examples were presented from disease transmission, social behavior, mutualistic interactions, and species migration. The five-minute, Ignite ESA format provided a fitting outlet for rapid presentation of methods, and opened lines of communication between somewhat disparate fields of study.

One major element that finds expression at road intersections, parks, gardens, square and open spaces in the urban landscape are outdoor sculptures. Of great significance is the historical information they disseminate, the visual impressions they convey and the aesthetic value they add to the quality of the city. From 1960s and after the civil war, the uses of sculptures for embellishments in public places have increased tremendously in Nigeria. However, outdoor sculpture for the purpose of recreation and relaxation in our built environment has not been adequately addressed scholastically in Nigeria. This paper, therefore, focuses on the social values derivable from the use of sculpture in urban design and the losses that could accrue to the social system if not adequately managed. The values of these sculptures to the socio-psychological development of Nigerians and the beautification of the urban environment are equally emphasized. The study shows that incorporating sculptures into public places without doubt will heighten public appreciation and aesthetic perception and make Nigerian cities unique and vibrant. Keywords: Nigeria urban cities; socio-psychological impact; outdoor sculptures.

Modeling the dynamics and walking accessibility of urban open spaces under various policy scenarios

Graph-based visibility analysis, developed from space syntax and social network theory, embraces mutual visibility between locations in a spatial system. It helps designers and researchers to decode spatial cognition and behavior, but methodological constraints limit its application to two-dimensional floor plans. In this study, we propose a new visibility graph analysis that can be used in three-dimensional built environments, such as multilevel atrium buildings or urban environments with canopies or overpass bridges. Furthermore, we draw a distinction between a generic visibility graph and a targeted visibility graph. In the former, an occupiable location is considered as both the origin and target of visibility lines. In the latter, we further take into account the visible space or specific targets in a system. Visible locations are spaces people can see but cannot necessarily physically occupy. With this differentiation, the visibility graph system is more amenable to new applications in three-dimensional architectural and urban design while retaining a mapping back to the original two-dimensional visibility graph method through the generic visibility graph. Four examples illustrate the application of the proposed visibility graph analysis in complex three-dimensional building and urban environments.

As an increasing numbers of people move into the cities, the need of places for community in such cities is required. Urban open spaces have already take a huge part in people`s daily life. It is expected that a high quality of places can be created for people. The urban open spaces design played an important role in modern urban design and planning. Squares and plazas developed a lot in city centres. But there is a problem that it is hard to build new open spaces in the historic city centres as the spaces is very limited. The genesis of this research came from two distinct sources. First, there are a number of factors which influence urban design. The surroundings, memories and the experiences of the city for people can be defined as contexts. ‘Contexts’ constrain and inform all areas of urban design action. Second, there was a need for people to have a special pleasure from the sight of public spaces. With a focus on the urban design, the main factors presented here are the open spaces. The role and meaning of the elements that play in urban design and the ways in which they are designed, developed and detailed are the most important elements for landscape architects to research and consider. In the end of this paper, the author developed a series of general design process and some design ideas as basis of design model of urban open space for the urban history context extending.

Network science established itself as a prominent tool for modeling time series and complex systems. This modeling process consists of transforming a set or a single time series into a network. Nodes may represent complete time series, segments, or single values, while links define associations or similarities between the represented parts. R is one of the main programming languages used in data science, statistics, and machine learning, with many packages available. However, no single package provides the necessary methods to transform time series into networks. This paper presents a detailed revision of the main transformation methods in the literature and their implementation in the ts2net package in R. The package provides time series distance functions that can be easily computed in parallel and in supercomputers to process larger data sets and methods to transform distance matrices into networks. ts2net also provides methods to transform a single time series into a network, such as recurrence networks, visibility graphs, and transition networks. Together with other packages, ts2net permits the use of network science and graph mining tools to extract information from time series.

Visibility algorithms are a family of methods that map time series into graphs, such that the tools of graph theory and network science can be used for the characterization of time series. This approach has proved a convenient tool, and visibility graphs have found applications across several disciplines. Recently, an approach has been proposed to extend this framework to multivariate time series, allowing a novel way to describe collective dynamics. Here we test their application to fMRI time series, following two main motivations, namely that (a) this approach allows vs to simultaneously capture and process relevant aspects of both local and global dynamics in an easy and intuitive way, and (b) this provides a suggestive bridge between time series and network theory that nicely fits the consolidating field of network neuroscience. Our application to a large open dataset reveals differences in the similarities of temporal networks (and thus in correlated dynamics) across resting-state networks, and gives indications that some differences in brain activity connected to psychiatric disorders could be picked up by this approach.