arXiv subjects

Bin Jiang

Publications and source records attributed to Bin Jiang.

161 records · Page 9Linked to original sources

arXiv2011

Exploring Human Mobility Patterns Based on Location Information of US Flights

A range of early studies have been conducted to illustrate human mobility patterns using different tracking data, such as dollar notes, cell phones and taxicabs. Here, we explore human mobility patterns based on massive tracking data of US flights. Both topological and geometric properties are examined in detail. We found that topological properties, such as traffic volume (between airports) and degree of connectivity (of individual airports), including both in- and outdegrees, follow a power law distribution but not a geometric property like travel lengths. The travel lengths exhibit an exponential distribution rather than a power law with an exponential cutoff as previous studies illustrated. We further simulated human mobility on the established topologies of airports with various moving behaviors and found that the mobility patterns are mainly attributed to the underlying binary topology of airports and have little to do with other factors, such as moving behaviors and geometric distances. Apart from the above findings, this study adopts the head/tail division rule, which is regularity behind any heavy-tailed distribution for extracting individual airports. The adoption of this rule for data processing constitutes another major contribution of this paper. Keywords: scaling of geographic space, head/tail division rule, power law, geographic information, agent-based simulations

physics.data-an↗

arXiv2011

AxialGen: A Research Prototype for Automatically Generating the Axial Map

AxialGen is a research prototype for automatically generating the axial map, which consists of the least number of the longest visibility lines (or axial lines) for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between closed spaces such as buildings and street blocks. This paper aims to provide an accessible guide to software AxialGen, and the underlying concepts and ideas. We concentrate on the explanation and illustration of the key concept of bucket: its definition, formation and how it is used in generating the axial map. Keywords: Bucket, visibility, medial axes, axial lines, isovists, axial map

cs.RO↗

arXiv2011

Defining and Generating Axial Lines from Street Center Lines for better Understanding of Urban Morphologies

Axial lines are defined as the longest visibility lines for representing individual linear spaces in urban environments. The least number of axial lines that cover the free space of an urban environment or the space between buildings constitute what is often called an axial map. This is a fundamental tool in space syntax, a theory developed by Bill Hillier and his colleagues for characterizing the underlying urban morphologies. For a long time, generating axial lines with help of some graphic software has been a tedious manual process that is criticized for being time consuming, subjective, or even arbitrary. In this paper, we redefine axial lines as the least number of individual straight line segments mutually intersected along natural streets that are generated from street center lines using the Gestalt principle of good continuity. Based on this new definition, we develop an automatic solution to generating the newly defined axial lines from street center lines. We apply this solution to six typical street networks (three from North America and three from Europe), and generate a new set of axial lines for analyzing the urban morphologies. Through a comparison study between the new axial lines and the conventional or old axial lines, and between the new axial lines and natural streets, we demonstrate with empirical evidence that the newly defined axial lines are a better alternative in capturing the underlying urban structure. Keywords: Space syntax, street networks, topological analysis, traffic, head/tail division rule

cs.CV↗

arXiv2010

Measuring Urban Sprawl Based on Massive Street Nodes and the Novel Concept of Natural Cities

In this paper, we develop a novel approach to measuring urban sprawl based on street nodes and naturally defined urban boundaries, both extracted from massive volunteered geographic information OpenStreetMap databases through some data-intensive computing processes. The street nodes are defined as street intersections and ends, while the naturally defined urban boundaries constitute what we call natural cities. We find that the street nodes are significantly correlated with population of cities. Based on this finding, we set street nodes as a proxy of population to measure urban sprawl. We further find that street nodes bear a significant linear relationship with city areal extents. In the plot with the x axis representing city areal extents, and the y axis street nodes, sprawling cities are located below the regression line. We verified the approach using urban areas and population from the US census, and then applied the approach to three European countries: France, Germany, and the United Kingdom for the categorization of natural cities into three classes: sprawling, compact, and normal. This categorization sets a uniform standard for cross comparing sprawling levels across an entire country. Keywords: Street networks, openstreetmap, volunteered geographic information, GIS

physics.data-an↗

arXiv2010

Computing the Fewest-turn Map Directions based on the Connectivity of Natural Roads

In this paper, we introduced a novel approach to computing the fewest-turn map directions or routes based on the concept of natural roads. Natural roads are joined road segments that perceptually constitute good continuity. This approach relies on the connectivity of natural roads rather than that of road segments for computing routes or map directions. Because of this, the derived routes posses the fewest turns. However, what we intend to achieve are the routes that not only possess the fewest turns, but are also as short as possible. This kind of map direction is more effective and favorable by people, because they bear less cognitive burden. Furthermore, the computation of the routes is more efficient, since it is based on the graph encoding the connectivity of roads, which is significantly smaller than the graph of road segments. We made experiments applied to eight urban street networks from North America and Europe in order to illustrate the above stated advantages. The experimental results indicate that the fewest-turn routes posses fewer turns and shorter distances than the simplest paths and the routes provided by Google Maps. For example, the fewest-turn-and-shortest routes are on average 15% shorter than the routes suggested by Google Maps, while the number of turns is just half as much. This approach is a key technology behind FromToMap.org - a web mapping service using openstreetmap data.

cs.CG↗

arXiv2010

Zipf's Law for All the Natural Cities in the United States: A Geospatial Perspective

This paper provides a new geospatial perspective on whether or not Zipf's law holds for all cities or for the largest cities in the United States using a massive dataset and its computing. A major problem around this issue is how to define cities or city boundaries. Most of the investigations of Zipf's law rely on the demarcations of cities imposed by census data, e.g., metropolitan areas and census-designated places. These demarcations or definitions (of cities) are criticized for being subjective or even arbitrary. Alternative solutions to defining cities are suggested, but they still rely on census data for their definitions. In this paper we demarcate urban agglomerations by clustering street nodes (including intersections and ends), forming what we call natural cities. Based on the demarcation, we found that Zipf's law holds remarkably well for all the natural cities (over 2-4 million in total) across the United States. There is little sensitivity for the holding with respect to the clustering resolution used for demarcating the natural cities. This is a big contrast to urban areas, as defined in the census data, which do not hold stable for Zipf's law. Keywords: Natural cities, power law, data-intensive geospatial computing, scaling of geographic space

physics.data-an↗

arXiv2010

Agent-based Simulation of Human Movement Shaped by the Underlying Street Structure

Relying on random and purposive moving agents, we simulated human movement in large street networks. We found that aggregate flow, assigned to individual streets, is mainly shaped by the underlying street structure, and that human moving behavior (either random or purposive) has little effect on the aggregate flow. This finding implies that given a street network, the movement patterns generated by purposive walkers (mostly human beings) and by random walkers are the same. Based on the simulation and correlation analysis, we further found that the closeness centrality is not a good indicator for human movement, in contrast to a long standing view held by space syntax researchers. Instead we suggest that Google's PageRank, and its modified version - weighted PageRank, betweenness and degree centralities are all better indicators for predicting aggregate flow.

physics.data-an↗

arXiv2009

Characterizing Human Mobility Patterns in a Large Street Network

Previous studies demonstrated empirically that human mobility exhibits Levy flight behaviour. However, our knowledge of the mechanisms governing this Levy flight behaviour remains limited. Here we analyze over 72 000 people's moving trajectories, obtained from 50 taxicabs during a six-month period in a large street network, and illustrate that the human mobility pattern, or the Levy flight behaviour, is mainly attributed to the underlying street network. In other words, the goal-directed nature of human movement has little effect on the overall traffic distribution. We further simulate the mobility of a large number of random walkers, and find that (1) the simulated random walkers can reproduce the same human mobility pattern, and (2) the simulated mobility rate of the random walkers correlates pretty well (an R square up to 0.87) with the observed human mobility rate.

physics.data-an↗

arXiv2009

Statistical Eigenmode Transmission over Jointly-Correlated MIMO Channels

We investigate MIMO eigenmode transmission using statistical channel state information at the transmitter. We consider a general jointly-correlated MIMO channel model, which does not require separable spatial correlations at the transmitter and receiver. For this model, we first derive a closed-form tight upper bound for the ergodic capacity, which reveals a simple and interesting relationship in terms of the matrix permanent of the eigenmode channel coupling matrix and embraces many existing results in the literature as special cases. Based on this closed-form and tractable upper bound expression, we then employ convex optimization techniques to develop low-complexity power allocation solutions involving only the channel statistics. Necessary and sufficient optimality conditions are derived, from which we develop an iterative water-filling algorithm with guaranteed convergence. Simulations demonstrate the tightness of the capacity upper bound and the near-optimal performance of the proposed low-complexity transmitter optimization approach.

cs.IT↗

arXiv2009

Automatic Generation of the Axial Lines of Urban Environments to Capture What We Perceive

Based on the concepts of isovists and medial axes, we developed a set of algorithms that can automatically generate axial lines for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between buildings, where people can freely move around. The generation of the axial lines has been a key aspect of space syntax research, conventionally relying on hand-drawn axial lines of an urban environment, often called axial map, for urban morphological analysis. Although various attempts have been made towards an automatic solution, few of them can produce the axial map that consists of the least number of longest visibility lines, and none of them really works for different urban environments. Our algorithms provide a better solution than existing ones. Throughout this paper, we have also argued and demonstrated that the axial lines constitute a true skeleton, superior to medial axes, in capturing what we perceive about the urban environment. Keywords: Visibility, space syntax, topological analysis, medial axes, axial lines, isovists

cs.CG↗

arXiv2008

Self-organized Natural Roads for Predicting Traffic Flow: A Sensitivity Study

In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a sensitivity study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both Annual Average Daily Traffic (AADT) and Global Positioning System (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our big surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial insights into the understanding of road networks and their traffic from the perspective of complex networks. Keywords: topological analysis, traffic flow, phase transition, small world, scale free, tipping point

physics.data-an↗

arXiv2008

Ranking Spaces for Predicting Human Movement in an Urban Environment

A city can be topologically represented as a connectivity graph, consisting of nodes representing individual spaces and links if the corresponding spaces are intersected. It turns out in the space syntax literature that some defined topological metrics can capture human movement rates in individual spaces. In other words, the topological metrics are significantly correlated to human movement rates, and individual spaces can be ranked by the metrics for predicting human movement. However, this correlation has never been well justified. In this paper, we study the same issue by applying the weighted PageRank algorithm to the connectivity graph or space-space topology for ranking the individual spaces, and find surprisingly that (1) the PageRank scores are better correlated to human movement rates than the space syntax metrics, and (2) the underlying space-space topology demonstrates small world and scale free properties. The findings provide a novel justification as to why space syntax, or topological analysis in general, can be used to predict human movement. We further conjecture that this kind of analysis is no more than predicting a drunkard's walking on a small world and scale free network. Keywords: Space syntax, topological analysis of networks, small world, scale free, human movement, and PageRank

physics.data-an↗

arXiv2008

Street Hierarchies: A Minority of Streets Account for a Majority of Traffic Flow

Urban streets are hierarchically organized in the sense that a majority of streets are trivial, while a minority of streets is vital. This hierarchy can be simply, but elegantly, characterized by the 80/20 principle, i.e. 80 percent of streets are less connected (below the average), while 20 percent of streets are well connected (above the average); out of the 20 percent, there is 1 percent of streets that are extremely well connected. This paper, using a European city as an example, examined, at a much more detailed level, such street hierarchies from the perspective of geometric and topological properties. Based on an empirical study, we further proved a previous conjecture that a minority of streets accounts for a majority of traffic flow; more accurately, the 20 percent of top streets accommodate 80 percent of traffic flow (20/80), and the 1 percent of top streets account for more than 20 percent of traffic flow (1/20). Our study provides new evidence as to how a city is (self-)organized, contributing to the understanding of cities and their evolution using increasingly available mobility geographic information.

physics.data-an↗

arXiv2007

The Flow Dimension and Capacity for Structuring Urban Street Networks

This paper aims to measure the efficiency of urban street networks (a kind of complex networks) from the perspective of the multidimensional chain of connectivity (or flow). More specifically, we define two quantities: flow dimension and flow capacity, to characterize structures of urban street networks. To our surprise for the topologies of urban street networks, previously confirmed as a form of small world and scale-free networks, we find that (1) the range of their flow dimension is rather wider than their random and regular counterparts, (2) their flow dimension shows a power-law distribution, and (3) they have a higher flow capacity than their random and regular counterparts. The findings confirm that (1) both the wider range of flow dimension and the higher flow capacity can be a signature of small world networks, and (2) the flow capacity can be an alternative quantity for measuring the efficiency of networks or that of the individual nodes. The findings are illustrated using three urban street networks (two in the Europe and one in the USA).

physics.data-an↗

arXiv2007

Street-based Topological Representations and Analyses for Predicting Traffic Flow in GIS

It is well received in the space syntax community that traffic flow is significantly correlated to a morphological property of streets, which are represented by axial lines, forming a so called axial map. The correlation co-efficient (R square value) approaches 0.8 and even a higher value according to the space syntax literature. In this paper, we study the same issue using the Hong Kong street network and the Hong Kong Annual Average Daily Traffic (AADT) datasets, and find surprisingly that street-based topological representations (or street-street topologies) tend to be better representations than the axial map. In other words, vehicle flow is correlated to a morphological property of streets better than that of axial lines. Based on the finding, we suggest the street-based topological representations as an alternative GIS representation, and the topological analyses as a new analytical means for geographic knowledge discovery.

physics.data-an↗

arXiv2007

A Topological Pattern of Urban Street Networks: Universality and Peculiarity

In this paper, we derive a topological pattern of urban street networks using a large sample (the largest so far to the best of our knowledge) of 40 U.S. cities and a few more from elsewhere of different sizes. It is found that all the topologies of urban street networks based on street-street intersection demonstrate a small world structure, and a scale-free property for both street length and connectivity degree. More specifically, for any street network, about 80% of its streets have length or degrees less than its average value, while 20% of streets have length or degrees greater than the average. Out of the 20%, there are less than 1% of streets which can form a backbone of the street network. Based on the finding, we conjecture that the 20% streets account for 80% of traffic flow, and the 1% streets constitute a cognitive map of the urban street network. We illustrate further a peculiarity about the scale-free property.

physics.data-an↗

arXiv2007

Spatial Topology and its Structural Analysis based on the Concept of Simplicial Complex

This paper introduces a model that identifies spatial relationships for a structural analysis based on the concept of simplicial complex. The spatial relationships are identified through overlapping two map layers, namely a primary layer and a contextual layer. The identified spatial relationships are represented as a simplical complex, in which simplices and vertices respectively represent two layers of objects. The model relies on the simplical complex for structural representation and analysis. To quantify structural properties of individual primary objects (or equivalently simplices), and the simplicial complex as a whole, we define a set of centrality measures by considering multidimensional chains of connectivity, i.e. the number of contextual objects shared by a pair of primary objects. With the model, the interaction and relationships with a geographic system are modeled from both local and global perspectives. The structural properties and modeling capabilities are illustrated with a simple example and a case study applied to the structural analysis of an urban system.

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