1,720,977 research outputs found
Foreword Proceedings of the 1st ACM SIGSPATIAL International Workshop on on Animal Movement Ecology and Human Mobility, HANIMOB 2021
No full textMovement ecology is a relatively new discipline in the field of ecology that studies the spatio-temporal patterns and processes at the basis of animal movement. Ecologists track animal movement using telemetry tools (such as for example bio-logging GPS tags), and then combine resulting trajectories with contextual data on environment, such as those collected through remote sensing. Combined data are then used to build statistical models that describe the determinants of animal movement, such as environmental constraints (e.g. snow layer, habitat fragmentation, human disturbance) or the inner status of individuals (e.g. memory, orientation capacity). Movement is also the focus of a different field of research, i.e. human mobility, which is studied in a set of disciplines, from GIScience, to computer science, physics, geography and transportation science. In analogy with movement ecology, human mobility benefited from the recent development of sensors capable of capturing human movement in real time and at detailed spatial and temporal scales (e.g. GPS trackers). While data and analytical methods are similar between movement ecology and human mobility, there is surprisingly little interdisciplinary awareness of these similarities. Recently, GIScientists have called for the establishment of the Integrated Science of Movement, with the specific aim to bridge the gap between movement ecology and human mobility and raise awareness of respective problems, data and methods. This would fundamentally help ecologists to improve their understanding of the impact of anthropogenic environmental change on animal movement in the Anthropocene. Indeed, ecologists measure wildlife-human interaction mainly via the collection of static (at least at high to intermediate temporal resolution) data from remote sensing sources (e.g. road maps, high resolution forest cover, etc.), to assess, for example, the effect of landscape fragmentation on migratory propensity. However, data on human presence and activity are intrinsically dynamic, rather than static. Developing new methods to implement such data (e.g. road traffic or human recreational activities) in the study of movement ecology would crucially improve the ecologists' understanding of the tight relationship between animal movement and human activities. In the wake of the COVID-19 pandemic, human mobility data, which were previously difficult to obtain, have become open and available and there is an opportunity to use these in conjunction with animal data to study wildlife-human interaction. This however requires bespoke complex spatio-temporal methods for both data fusion and analysis that currently do not exist. Solving this challenge is crucial for movement ecology investigation, as for example to unveil the effect of COVID-19 human lockdowns on animal movement and behavior. By introducing a specific ecology problem to the GIS scientists and spatial computing scientists, we hope to kick-start an interdisciplinary effort to develop methods, metrics and other solutions that will integrate analysis of dynamic anthropogenic activity, such as human mobility, into the study of animal movement
Periodic stops discovery through density-based trajectory segmentation
No full textStop-and-move is a popular mobility pattern describing the behavior of an object alternating periods of relative stationarity (stops) with periods of mobility (move). In this demo, we present a system supporting the discovery of periodic stops in regions with uncertain boundaries, such as the animal home-ranges and the attraction areas in a city. This system is built on recent results showing the effectiveness of a density-based trajectory segmentation technique for the discovery of derived patterns defined in terms of stops with noise. This demo illustrates the architecture developed on top of the existing MigrO platform, and exemplifies the periodic stop discovery process on real data about birds migration
Segmentation techniques for the summarization of individual mobility data
Full text linkSegmentation techniques partition a sequence of data points into a series of disjoint subsequences-segments-based on some criteria. Depending on the context and the nature of data themselves, segments return an approximate representation. The final result is a summarized representation of the sequence. This intuitive mechanism has been extensively studied, for example, for the summarization of time series in order to preserve the 'shape' of the sequence while omitting irrelevant details. This survey focuses on the use of segmentation methods for extracting behavioral information from individual mobility data, in particular from spatial trajectories. Such information can then be given a compact representation in the form of summarized trajectories, e.g., semantic trajectories and symbolic trajectories. Two major streams of research are discussed, spanning computational geometry and data mining respectively, that are emblematic of the multiplicity of views
Discovering gatherings based on individual mobility patterns: challenges and direction
No full textGiven a database of spatial trajectories reporting the movement of a set of objects in a time frame, the problem is to discover the groups of objects that stay in close proximity within a geographical area for a significant time. To deal with the problem, techniques for the discovery of collective patterns, e.g. the meeting pattern, have been proposed. Such techniques, however, impose stringent constraints on the object movement. In this paper we investigate a generalized, flexible approach that builds on the idea of expressing the collective pattern as sum of individual behaviors. We present a technique called k-Gathering for the discovery of gatherings of at least k objects, which leverages a recent method for the discovery of stop-and-move patterns. The experiments, conducted on both synthetic and real data, show that the direction is promising and that the approach can be effective also on low sampling rate trajectories
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Multi-scale framework for attraction place identification across human and animal mobility
No full textA large volume of research has been devoted to the concept of mobility, a theme that is transversal to multiple fields of study and applications, from biology and ecology, to computer science and economy. Despite the considerable efforts made by a few scientific communities and the relevant results obtained so far, only very recently the issue of adopting a unifying and comprehensive approach across has been faced. In this paper, we present an overview of the quantitative framework we have recently developed to analyse and model human mobility, based on symbolic trajectories built on CDR data (Call Detail Record) provided by a telco operator [5]. Driven by a location-centric perspective, the framework includes a novel trajectory summarization technique for the extraction of the locations of interest from symbolic trajectories, a relevance analysis providing a novel location taxonomy and, inspired by ecological studies, a diversity analysis to characterize the movement through a location diversity profile. The ultimate goal of this contribution is to stress the need of a methodological integration between human and animal mobility analytical methods
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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