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Stacked space-time densities: a geovisualisation approach to explore dynamics of space use over time / Urška Demšar in Geoinformatica, vol 19 n° 1 (January - March 2015)  

Public [article]  inGeoinformatica > vol 19 n° 1 (January - March 2015) . - pp 85 - 115 Titre : Stacked space-time densities: a geovisualisation approach to explore dynamics of space use over time Type de document : Article/Communication Auteurs : Urška Demšar, Auteur ; Kevin Buchin, Auteur ; E. Emiel Van Loon, Auteur ; Judy Shamoun-Baranes, Auteur Année de publication : 2015 Article en page(s) : pp 85 - 115 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] agrégation spatiale [Termes IGN] agrégation temporelle [Termes IGN] analyse spatio-temporelle [Termes IGN] Aves [Termes IGN] cube espace-temps [Termes IGN] densité [Termes IGN] distance de propagation [Termes IGN] données spatiotemporelles [Termes IGN] estimation par noyau [Termes IGN] migration animale [Termes IGN] positionnement cinématique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Recent developments and ubiquitous use of global positioning devices have revolutionised movement ecology. Scientists are able to collect increasingly larger movement datasets at increasingly smaller spatial and temporal resolutions. These data consist of trajectories in space and time, represented as time series of measured locations for each tagged animal. Such data are analysed and visualised using methods for estimation of home range or utilisation distribution, which are often based on 2D kernel density in geographic space. These methods have been developed for much sparser and smaller datasets obtained through very high frequency (VHF) radio telemetry. They focus on the spatial distribution of measurement locations and ignore time and sequentiality of measurements. We present an alternative geovisualisation method for spatio-temporal aggregation of trajectories of tagged animals: stacked space-time densities. The method was developed to visually portray temporal changes in animal use of space using a volumetric display in a space-time cube. We describe the algorithm for calculation of stacked densities using four different decay functions, normally used in space use studies: linear decay, bisquare decay, Gaussian decay and Brownian decay. We present a case study, where we visualise trajectories of lesser black backed gulls, collected over 30 days. We demonstrate how the method can be used to evaluate temporal site fidelity of each bird through identification of two different temporal movement patterns in the stacked density volume: spatio-temporal hot spots and spatial-only hot spots. Numéro de notice : A2015-486 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0207-5 Date de publication en ligne : 03/04/2014 En ligne : https://doi.org/10.1007/s10707-014-0207-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77249 [article]

Processing aggregated data: the location of clusters in health data / Kevin Buchin in Geoinformatica, vol 16 n° 3 (July 2012)  

Public [article]  inGeoinformatica > vol 16 n° 3 (July 2012) . - pp 197 - 521 Titre : Processing aggregated data: the location of clusters in health data Type de document : Article/Communication Auteurs : Kevin Buchin, Auteur ; M. Buchin, Auteur ; Marc Van Kreveld, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 197 - 521 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] agrégation spatiale [Termes IGN] base de données spatiotemporelles [Termes IGN] base de données thématiques [Termes IGN] géopositionnement [Termes IGN] regroupement de données [Termes IGN] santé Résumé : (Auteur) Spatially aggregated data is frequently used in geographical applications. Often spatial data analysis on aggregated data is performed in the same way as on exact data, which ignores the fact that we do not know the actual locations of the data. We here propose models and methods to take aggregation into account. For this we focus on the problem of locating clusters in aggregated data. More specifically, we study the problem of locating clusters in spatially aggregated health data. The data is given as a subdivision into regions with two values per region, the number of cases and the size of the population at risk. We formulate the problem as finding a placement of a cluster window of a given shape such that a cluster function depending on the population at risk and the cases is maximized. We propose area-based models to calculate the cases (and the population at risk) within a cluster window. These models are based on the areas of intersection of the cluster window with the regions of the subdivision. We show how to compute a subdivision such that within each cell of the subdivision the areas of intersection are simple functions. We evaluate experimentally how taking aggregation into account influences the location of the clusters found. Numéro de notice : A2012-108 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-011-0143-6 En ligne : https://doi.org/10.1007/s10707-011-0143-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31556 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-2012031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Constrained free space diagrams: a tool for trajectory analysis / Kevin Buchin in International journal of geographical information science IJGIS, vol 24 n°7-8 (july 2010)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 24 n°7-8 (july 2010) . - pp 1101 - 1125 Titre : Constrained free space diagrams: a tool for trajectory analysis Type de document : Article/Communication Auteurs : Kevin Buchin, Auteur ; M. Buchin, Auteur ; J. Gudmundsson, Auteur Année de publication : 2010 Article en page(s) : pp 1101 - 1125 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] courbe [Termes IGN] diagramme [Termes IGN] direction [Termes IGN] objet mobile [Termes IGN] similitude [Termes IGN] trajet (mobilité) [Termes IGN] vitesse Résumé : (Auteur) Time plays an important role in the analysis of moving object data. For many applications it is not sufficient to only compare objects at exactly the same times, or to consider only the geometry of their trajectories. We show how to leverage between these two approaches by extending a tool from curve analysis, namely the free space diagram. Our approach also allows us to take further attributes of the objects like speed or direction into account. We demonstrate the usefulness of the new tool by applying it to the problem of detecting single file movement. A single file is a set of moving entities, which are following each other, one behind the other. Our algorithm is the first one developed for detecting such movement patterns. For this application, we analyse demonstrate the performance of our tool both theoretically experimentally. Numéro de notice : A2010-322 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810903569598 En ligne : https://doi.org/10.1080/13658810903569598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30516 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2010041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2010042	RAB	Revue	Centre de documentation	En réserve L003	Disponible