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

Abstract. 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 2-dimentianal undirected 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 travel – street intersections and POIs, origins, and destinations of travel, by connecting these potential observer’s decision locations in an open space between buildings. 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.

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

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Performance of a range of urban amenities is influenced by their accessibility to pedestrians. Success in attracting pedestrians to a particular location depends on how they project visuospatial information. In this paper, we propose an original method for analysing the visuospatial integration of particular locations within a street network. As a case study we analyse the distribution of one type of urban amenities - food and drink public facilities. We represent them in a form of visibility graph as objects of navigational decisions within the street network. To explore how urban facilities, streets and pedestrian visual cognition are interrelated, we create and compare three cases: a street network visibility graph and two visibility graphs of amenities. The first graph is based on the existing, “natural” distribution, while the second is an “artificial”, fabricated version of the environment, where urban locations are redistributed evenly across the case study. We study the graphs’ global network properties by the use of small-world, and scale-free models. Our results demonstrate that views available for an urban traveller in the existing, “natural” setting had a particular structure. It is built of numerous weakly connected locations coexisting with a small number of hubs with an exceptionally large number of visual connections. Such organisation of urban visibility shows that visuospatial network shares morphological similarities with other natural networks, suggesting that common organizational principles underlie network structure.

The average speed and density of road transport are used as indicators of the congestion situation, but do not allow tracking the evolution (stages of formatting, progressing, and vanishing) of traffic congestion. The authors proposed and justified a quantitative indicator of traffic congestion, which allows in an automated mode to identify the congestion situation on the urban road network using hardware and software video recording systems. The purpose of this study is due to the need to study the quantitative characteristics of the proposed indicator at characteristic intersections of urban roads, which will allow us to develop scientifically based recommendations for predicting congestion situations, substantiating, and making optimal decisions on measures to promptly eliminate traffic congestion. The object of study is the traffic flow at three types of intersections of the Perm city road network, equipped with a photo and video recording software and hardware complex. The subject of the study is the regularities of the evolution of the listed deterministic indicators of traffic flows, which can be used for operational forecasting of the formation, development, and elimination of traffic congestion. The theoretical and methodological approach is based on the methods of mathematical statistics used to process the results of observations of traffic flows at different types of intersections using a «sliding window», calculating the average daily value and standard deviation. The initial data were obtained with the help of hardware and software complexes for fixing violations of traffic rules installed on the street and road network of the Perm city. As a result of the study, the rational parameters of the «sliding window» were determined, ensuring the structuring of the traffic congestion indicator; the facts of the congestion situations formation were revealed; the features of the congestion evolution and the presence of problematic traffic directions for which it is advisable to change the traffic light regulation mode were determined. The theoretical and practical significance of the work consists in checking the operability of the proposed indicator and criterion of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, adjusting the operating modes of traffic lights, etc. It is also possible to use the proposed traffic congestion indicator to assess the effectiveness of traffic light regulation on the Perm city road network. The direction of further research is to study the patterns of traffic congestion at intersections of the urban road network, of various types that are not included in this study.

Road networks are a classical stage for applications in network science and graph theory. Meanwhile, many combinatorial problems that arise in road networks are computationally intractable. Thus, an attractive way of tackling them is through efficient heuristics with provable performance guarantees, better known as approximation algorithms. This motivates the intersection of algorithm design with the aforementioned fields. Specifically, identifying measures that characterize graphs and exploiting them in the design of algorithms may yield practical heuristics with rigorous mathematical justification. Herein, we propose a new graph measure, namely the asymmetry factor ΔG of a directed graph G, with immediate algorithmic results via a symmetrization procedure and the black box use of approximation algorithms for symmetric graphs. Crucially, we analyze the asymmetry factors of the road networks from a diverse set of twelve cities, providing empirical evidence that road networks exhibit low bounded asymmetry and thereby justifying the practical use of algorithms for symmetric graphs.

Information sources have developed considerably in recent years; many electronic platforms are able to provide valuable information regards engineering topics. One of the most important data sources is the open street map (OSM) platform, providing editable geographic information for most of the world, with different levels of accuracy and at different points in time. Road network mapping requires a high level of effort and accuracy, due to the complexity of the modelling and the amount of information that needs to be included in the feature class. OSM can support road network modelling by providing a different kind of data. In this paper, a systematic procedure was investigated for the production of an automated road network for Basrah city, as a case study for the use of OSM in Geographic Information System (GIS) 10.8 software. Specific spatial analysis tools such as road density and network analysis were also implemented. This study validated a computerised procedure to extract OSM data via two methods of validation and demonstrated the immediate applicability of this data for density and network analysis. The research results show a significant reduction in time and effort required to produce an accurate Basrah city road network using OSM data sources. Density analysis and network analysis show the importance and validity of the produced road network.

The stages of traffic management in the perspective of the use of unmanned road transport on the street and road network of large cities are considered, the results of visual observations of the movement of single cars and traffic flow in general are presented, shortcomings in the organization of traffic are identified, the causes of starting delays at intersections are determined. A variant of the order of access to a regulated intersection and exit from it by motor transport is considered. It is proposed to fix such a variant of the passage of a regulated intersection in the Traffic Rules of the Russian Federation. It is proposed to make changes and additions to paragraph 6.14 of the Traffic Rules of the Russian Federation. Keywords road network, vehicle, road intersection, left turn, starting delay

Functional connectivity related to road linear erosion at rainfall event scale in an agricultural watershed on the Loess Plateau

Extracting highly detailed and accurate road network information from crowd-sourced vehicle trajectory data, which has the advantages of being low cost and able to update fast, is a hot topic. With the rapid development of wireless transmission technology, spatial positioning technology, and the improvement of software and hardware computing ability, more and more researchers are focusing on the analysis of Global Positioning System (GPS) trajectories and the extraction of road information. Road intersections are an important component of roads, as they play a significant role in navigation and urban planning. Even though there have been many studies on this subject, it remains challenging to determine road intersections, especially for crowd-sourced vehicle trajectory data with lower accuracy, lower sampling frequency, and uneven distribution. Therefore, we provided a new intersection-first approach for road network generation based on low-frequency taxi trajectories. Firstly, road intersections from vector space and raster space were extracted respectively via using different methods; then, we presented an integrated identification strategy to fuse the intersection extraction results from different schemes to overcome the sparseness of vehicle trajectory sampling and its uneven distribution; finally, we adjusted road information, repaired fractured segments, and extracted the single/double direction information and the turning relationships of the road network based on the intersection results, to guarantee precise geometry and correct topology for the road networks. Compared with other methods, this method shows better results, both in terms of their visual inspections and quantitative comparisons. This approach can solve the problems mentioned above and ensure the integrity and accuracy of road intersections and road networks. Therefore, the proposed method provides a promising solution for enriching and updating navigable road networks and can be applied in intelligent transportation systems.

This paper interprets ancient public space as a material correlate of civic communities, using the Late Bronze Age city of Ugarit as a case-study. Civic communities acted as significant political factor throughout the history of the ancient Near East, both as institutions (e.g., political assemblies) and as informal groups (the “town's crowd”). A growing body of evidence and innovative approaches shows that, particularly in the Upper Syrian Euphrates region of the Late Bronze Age (cf. above all Tell Bazi and Emar), these forms of social aggregation and political negotiation were influential and sometimes antagonistic alternatives to monarchical powers. In this paper, I approach the study of past communal political life by analyzing with an integrated, GIS-based methodology the planning and use of public squares at Ugarit. The contribution aims at highlighting the relevance of public space for understanding the balance of power in the cities of the Late Bronze Age and discussing the chances and limits of relating civic politics to specific features of the ancient urban design.

Predicting traffic speed is of importance in transportation management. Signalized road networks manifest highly dynamic speed patterns that are challenging to model and predict. We propose a hybrid deep-learning-based approach for link speed prediction, aiming at capturing heterogeneous spatiotemporal correlations between road intersections. After transforming original road networks and intersections into graphs, this approach leverages a layered graph convolution network structure to model traffic speed variations at both intersection and road network levels. The two levels are combined through a fully connected neural layer. Neural spatiotemporal attention mechanisms are applied to modulate the most relevant periodical traffic information during signal cycles. The proposed approach was evaluated using real-world speed data collected in Hangzhou City, China. Experiments demonstrate that the proposed approach can offer a scalable and effective solution for predicting short-term speed for signalized road networks.

The aim of this study is to analyze the structure of the road network in As-Salt City in the period between 2004 and 2016, in order to identify the road employability in terms of the degree of connectivity, rotation, accessibility, and density. The relationship between the social properties and road distribution are also examined through analysis of the network characteristics concerning population distribution. The data used in this study was based on the As-Salt City Municipality Database supported with fieldwork done in 2016. The network analysis approach using GIS was used to calculate the roads employability.
 
 The study compares between the results of the analysis using the cognitive model of the road network for the years 2004 and 2016, knowing that the number of nodes in 2004 and 2016 was constant indicating the number of neighborhoods is 20, while the number of links changed from 42 links in 2004 to 50 links in 2016 and the average center of roads was determined, and it was estimated that the average road center is located near the municipality of As-Salt
 
 The study indicates that the road network suffers from a low degree of communication and rotation and the standard distance of road sites in the study area. The standard distance for each group was 2338.49 m. There is a disparity in the distribution of road network within As-Salt City, and the proportion of roads lengths dose not suit the population distribution pattern. The neighborhood of Al- Salalem, includes 19.5% of the total number of roads in As-Salt, because the neighborhood of Al-Salalem contains the highest population census and this is accompanied by urban growth, which is necessarily accompanied by the presence of roads. Therefore, it is recommended to have a plan to redistribute the population in the city and to establish new roads to reduce the problems of traffic in the city.

The article presents the author's approach to the pre-project analysis of the passenger service schemes on suburban, intercity and international road transport. Studies on the directions and volume of traffic were carried out in several Urals cities. A bus traffic model from federal and regional roads to the bus station down the city's road network has been developed. The article presents the algorithm for conducting a study of the bus traffic order from the bus station down the big city’s network of roads. The fundamental principles of the logistics approach to optimizing the region route network were established.

<div class="section abstract"><div class="htmlview paragraph">Presently, the visibility graphs algorithm is mainly applied for path planning of indoor mobile robot. It only considers the constraints such as travelling time and move distance. The road lane and vehicle dynamics constraints are not deal with usually. In this paper, a local path planning algorithm based on improved visibility graphs is proposed for intelligent vehicle on structured road. First, free state space (FSS) is established based on ago-vehicle state, road lane and traffic condition for permitting ago-vehicle move safely. In FSS, the vehicle’s maneuver in preview distance can be inferred and the local target point can be designated. Next, sampling points is created in FSS. Combined with local target point, initial point and sampling points, road network can be generated consequently. Then, the approachable path in the road network are evaluated by constrains of the Euclidean distance and the vehicle dynamics constraints. In this way the unique shortest path satisfying the constraints are generated as an optimal path. Finally, the efficiency and performance of the algorithm are validated by simulation results. The comparison results with RRT algorithm show that, the planned path achieved by improved visibility graphs has shorter travel distance and lower curvature, which shows more superior advantage for the path planning of intelligent vehicle than RRT.</div></div>