A heuristic alpha-shape based clustering method for ranked radial pattern data

Mu, Lan; Liu, Rongzeng

doi:10.1016/j.apgeog.2010.11.012

Cited by 9 publications

(8 citation statements)

References 32 publications

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“…The edge weights follow a power law distribution ( Figure 4B ). It is similar to the spatial interaction distributions identified from different data sets [15] , [16] , [32] . Kang et al have argued that such a power law distribution mainly derives from the city size distribution, given that its distance decay effect is weak [15] .…”

Section: Resultssupporting

confidence: 71%

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

et al. 2014

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The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.

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Section: Resultssupporting

confidence: 71%

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

et al. 2014

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“…Nevertheless we decided to use this estimator in our current study, as it is the only implementation of a detailed polygon descriptor that is readily available to field biologists. As other studies point out, it is likely that other, similar descriptors [40], [64] will perform equally well or better [65]. We urge developers to make their methods and algorithms openly available and implement them for use in widespread software environments.…”

Section: Discussionmentioning

confidence: 96%

“…5B, 10A), which, on the other hand, faces two caveats. Unlike other detailed descriptors of point patterns, and due to the manufacturer’s copyright policy, DH as implemented in ‘XToolsPro’ [55] is not ‘open source’, although some information regarding the underlying algorithm [56] was disclosed ([65] and personal communication with Data East). Nevertheless we decided to use this estimator in our current study, as it is the only implementation of a detailed polygon descriptor that is readily available to field biologists.…”

Section: Discussionmentioning

confidence: 99%

“…The minimal number of equiangular intrusion trials that generally has to be performed to reach concise conclusions about relative territory size was evaluated by examining the asymptotic behaviour and rank-order of averaged area accumulation curves of the DH estimator for each shape. This estimator was chosen based on the previously described strong dependence of polygon estimators on the number of points used, where detailed hull methods better fit concave shapes compared to MCPs [40] , [42] , [63] – [65] .…”

Section: Methodsmentioning

confidence: 99%

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Intrusion Experiments to Measure Territory Size: Development of the Method, Tests through Simulations, and Application in the Frog Allobates femoralis

Ringler

Mendoza

et al. 2011

PLoS ONE

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Territoriality is a widespread behaviour in animals and its analysis is crucial in several areas of behavioural, ecological and evolutionary research. Commonly, territory size is assessed through territory mapping and the application of simple area estimators such as minimum convex polygons. In the present study we demonstrate that territory size can be determined adequately with an active approach through intrusion experiments, a technique that is commonly used in behavioural research in other contexts. Tests with simulated data indicate that a minimum of twelve trials needs to be performed to establish reliable orders of relative territory size. To estimate absolute territory size, detailed hull techniques are most appropriate when analyzing point patterns of intrusion experiments, while the local convex hull estimator enables the construction of internal utilization distributions based on such point patterns. Additionally we suggest a ‘stretch the centre’ approach to emphasize the actual process of intrusion experiments in the construction of internal utilization distributions. To demonstrate the utility of the method, we apply all findings from the simulations to data from fieldwork with the model species Allobates femoralis, a territorial aromobatid frog from the lowland rainforest of French Guiana.

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“…α-shapes were earlier used for clustering and classification in [31,33,37]; however, the problems considered in these papers, as well as their solutions, are completely different from ours. Mu and Liu [33] assumed that a "rank" is given for every data point; then for every rank r they compute the α-shape for points of rank ≤ r, obtaining a sequence of α-shapes of increasing α (we do not have any ranks in the input). Lucieer and Kraak [31] used α-shapes to define shapes in the feature space of remotely sensed images; they then classified new images using the distances to the α-shapes.…”

Section: Introductionmentioning

confidence: 86%

Visual Analytics for Spatial Clustering: Using a Heuristic Approach for Guided Exploration

Packer¹,

Bak²,

Nikkilä

et al. 2013

IEEE Trans. Visual. Comput. Graphics

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We propose a novel approach of distance-based spatial clustering and contribute a heuristic computation of input parameters for guiding users in the search of interesting cluster constellations. We thereby combine computational geometry with interactive visualization into one coherent framework. Our approach entails displaying the results of the heuristics to users, as shown in Figure 1, providing a setting from which to start the exploration and data analysis. Addition interaction capabilities are available containing visual feedback for exploring further clustering options and is able to cope with noise in the data. We evaluate, and show the benefits of our approach on a sophisticated artificial dataset and demonstrate its usefulness on real-world data.

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A heuristic alpha-shape based clustering method for ranked radial pattern data

Cited by 9 publications

References 32 publications

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

Intrusion Experiments to Measure Territory Size: Development of the Method, Tests through Simulations, and Application in the Frog Allobates femoralis

Visual Analytics for Spatial Clustering: Using a Heuristic Approach for Guided Exploration

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