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Measuring dynamic interaction in movement data / Jed A. Long in Transactions in GIS, vol 17 n° 1 (February 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 1 (February 2013) . - pp 62 - 77 Titre : Measuring dynamic interaction in movement data Type de document : Article/Communication Auteurs : Jed A. Long, Auteur ; T. Nelson, Auteur Année de publication : 2013 Article en page(s) : pp 62 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] données localisées dynamiques [Termes IGN] interaction spatiale [Termes IGN] objet mobile Résumé : (Auteur) The emergence of technologies capable of storing detailed records of object locations has presented scientists and researchers with a wealth of data on object movement. Yet analytical methods for investigating more advanced research questions from such detailed movement datasets remain limited in scope and sophistication. Recent advances in the study of movement data has focused on characterizing types of dynamic interactions, such as single-file motion, while little progress has been made on quantifying the degree of such interactions. In this article, we introduce a new method for measuring dynamic interactions (termed DI) between pairs of moving objects. Simulated movement datasets are used to compare DI with an existing correlation statistic. Two applied examples, team sports and wildlife, are used to further demonstrate the value of the DI approach. The DI method is advantageous in that it measures interaction in both movement direction (termed azimuth) and displacement. Also, the DI approach can be applied at local, interval, episodal, and global levels of analysis. However the DI method is limited to situations where movements of two objects are recorded at simultaneous points in time. In conclusion, DI quantifies the level of dynamic interaction between two moving objects, allowing for more thorough investigation of processes affecting interactive moving objects. Numéro de notice : A2013-040 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01353.x Date de publication en ligne : 09/10/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01353.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32178 [article]

Predicting forest age classes from high spatial resolution remotely sensed imagery using Voronoi polygon aggregation / T. Nelson in Geoinformatica, vol 8 n° 2 (June - August 2004)  

Public [article]  inGeoinformatica > vol 8 n° 2 (June - August 2004) Titre : Predicting forest age classes from high spatial resolution remotely sensed imagery using Voronoi polygon aggregation Type de document : Article/Communication Auteurs : T. Nelson, Auteur ; B. Boots, Auteur ; Michael A. Wulder, Auteur ; R. Feick, Auteur Année de publication : 2004 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] agrégation de données [Termes IGN] dendrochronologie [Termes IGN] diagramme de Voronoï [Termes IGN] forêt [Termes IGN] image à résolution métrique [Termes IGN] image Ikonos [Termes IGN] image panchromatique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] peuplement végétal [Termes IGN] polygone [Termes IGN] sylviculture Résumé : (Auteur) Efficient identification of forest age is useful for forest management and ecological applications. Here, we propose a user-assisted method for determining forest age using high spatial resolution remotely sensed imagery. This method requires individual trees to be extracted from imagery and represented as points. We use a local maximum filter to generate points that are converted to Voronoi polygons. Properties of the Voronoi polygons are correlated with forest age and used to aggregate points (trees) into areas (stands) based on three forest age classes. Accuracy of the aggregation ranges from approximately 68% to 78% and identification of the mature class is more consistent and accurate than the younger classes. Numéro de notice : A2004-168 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1023/B:GEIN.0000017745.92969.31 En ligne : https://doi.org/10.1023/B:GEIN.0000017745.92969.31 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26695 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-04021	RAB	Revue	Centre de documentation	En réserve L003	Disponible