This page has only limited features, please log in for full access.
Location-based social media have facilitated us to bridge the gap between virtual and physical worlds through the exploration of human online dynamics from a geographic perspective. This study uses a large collection of geotagged photos from Flickr to investigate the complexity of spatial interactions at the country level. We adopted three levels of administrative divisions in mainland China—province, city, and county—as basic geographic units and established three types of topology—province–province network, city–city network, and county–county network—from the extracted user movement trajectories. We conducted the scaling analysis based on heavy-tailed distribution statistics including power law exponents, goodness of fit index, and ht-index, by which we characterized a great complexity of the trajectory lengths, spatial distribution of geotagged photos, and the related metrics of built networks. The great complexity indicates the highly imbalanced ratio of populated-to-unpopulated areas or large-to-small flows between areas. More interestingly, all power law exponents were around 2 for the networks at various spatial and temporal scales. Such a recurrence of scaling statistics at multiple resolutions can be regarded a statistical self-similarity and could thus help us to reveal the fractal nature of human mobility patterns.
Wei Zhu; Ding Ma; Zhigang Zhao; Renzhong Guo. Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data. Sustainability 2020, 12, 9778 .
AMA StyleWei Zhu, Ding Ma, Zhigang Zhao, Renzhong Guo. Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data. Sustainability. 2020; 12 (22):9778.
Chicago/Turabian StyleWei Zhu; Ding Ma; Zhigang Zhao; Renzhong Guo. 2020. "Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data." Sustainability 12, no. 22: 9778.
Map generalization is a process of reducing the contents of a map or data to properly show a geographic feature(s) at a smaller extent. Over the past few years, the fractal way of thinking has emerged as a new paradigm for map generalization. A geographic feature can be deemed as a fractal given the perspective of scaling, as its rough, irregular, and unsmooth shape inherently holds a striking scaling hierarchy of far more small elements than large ones. The pattern of far more small things than large ones is a de facto heavy tailed distribution. In this paper, we apply the scaling hierarchy for map generalization to polygonal features. To do this, we firstly revisit the scaling hierarchy of a classic fractal: the Koch Snowflake. We then review previous work that used the Douglas–Peuker algorithm, which identifies characteristic points on a line to derive three types of measures that are long-tailed distributed: the baseline length (d), the perpendicular distance to the baseline (x), and the area formed by x and d (area). More importantly, we extend the usage of the three measures to other most popular cartographical generalization methods; i.e., the bend simplify method, Visvalingam–Whyatt method, and hierarchical decomposition method, each of which decomposes any polygon into a set of bends, triangles, or convex hulls as basic geometric units for simplification. The different levels of details of the polygon can then be derived by recursively selecting the head part of geometric units and omitting the tail part using head/tail breaks, which is a new classification scheme for data with a heavy-tailed distribution. Since there are currently few tools with which to readily conduct the polygon simplification from such a fractal perspective, we have developed PolySimp, a tool that integrates the mentioned four algorithms for polygon simplification based on its underlying scaling hierarchy. The British coastline was selected to demonstrate the tool’s usefulness. The developed tool can be expected to showcase the applicability of fractal way of thinking and contribute to the development of map generalization.
Ding Ma; Zhigang Zhao; Ye Zheng; Renzhong Guo; Wei Zhu. PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy. ISPRS International Journal of Geo-Information 2020, 9, 594 .
AMA StyleDing Ma, Zhigang Zhao, Ye Zheng, Renzhong Guo, Wei Zhu. PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy. ISPRS International Journal of Geo-Information. 2020; 9 (10):594.
Chicago/Turabian StyleDing Ma; Zhigang Zhao; Ye Zheng; Renzhong Guo; Wei Zhu. 2020. "PolySimp: A Tool for Polygon Simplification Based on the Underlying Scaling Hierarchy." ISPRS International Journal of Geo-Information 9, no. 10: 594.
Urban form can be reflected by many city elements, such as streets. A street network serves as the backbone of a city and reflects a city’s physical structure. A street network’s topological measures and statistical distributions have been widely investigated in recent years, but previous studies have seldom characterized the heavy-tailed distribution of street connectivities from a fractal perspective. The long-tail distribution of street connectivities can be fractal under the new, third definition: a set or pattern is fractal if the scaling of far more small things than large ones recurs at least twice. The number of recurred scaling patterns of far more less-connected streets than well-connected ones greatly helps in measuring the scaling hierarchy of a street network. Moreover, it enables us to examine the potential fractality of urban street networks at the national scale. In this connection, the present study aims to contribute to urban morphology in China through the investigation of the ubiquity of fractal cities from the lens of street networks. To do this, we generate hundreds of thousands of natural streets from about 4.5 million street segments over 298 Chinese cities and adopted power-law detection as well as three fractal metrics that emerged from the third definition of fractal. The results show that almost all cities bear a fractal structure in terms of street connectivities. Furthermore, our multiple regression analysis suggests that the fractality of street networks is positively correlated with urban socioeconomic status and negatively correlated with energy consumption. Therefore, the fractal metrics can be a useful supplement to traditional street-network configuration measures such as street lengths.
Ding Ma; Renzhong Guo; Ye Zheng; Zhigang Zhao; Fangning He; Wei Zhu. Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities. ISPRS International Journal of Geo-Information 2020, 9, 192 .
AMA StyleDing Ma, Renzhong Guo, Ye Zheng, Zhigang Zhao, Fangning He, Wei Zhu. Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities. ISPRS International Journal of Geo-Information. 2020; 9 (4):192.
Chicago/Turabian StyleDing Ma; Renzhong Guo; Ye Zheng; Zhigang Zhao; Fangning He; Wei Zhu. 2020. "Understanding Chinese Urban Form: The Universal Fractal Pattern of Street Networks over 298 Cities." ISPRS International Journal of Geo-Information 9, no. 4: 192.