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Reintroduction of the European bison (Bison bonasus) in central-eastern Europe: a case study / Cathlin M. Lord in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)
[article]
Titre : Reintroduction of the European bison (Bison bonasus) in central-eastern Europe: a case study Type de document : Article/Communication Auteurs : Cathlin M. Lord, Auteur ; Kylie P. Wirebach, Auteur ; Jennifer Tompkins, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1628 - 1647 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] analyse multicritère
[Termes IGN] analyse spatiale
[Termes IGN] biodiversité
[Termes IGN] combinaison linéaire ponderée
[Termes IGN] écosystème
[Termes IGN] Europe centrale
[Termes IGN] faune
[Termes IGN] habitat animal
[Termes IGN] Lettonie
[Termes IGN] politique de conservation (biodiversité)
[Termes IGN] Pologne
[Termes IGN] population animale
[Termes IGN] processus de hiérarchisation analytiqueRésumé : (auteur) European bison (Bison bonasus), a flagship species for the burgeoning re-wildling movement, faced challenges common to large mammals globally. These include deforestation, land use conversion, poaching, and a lack of genetic diversity. Despite these limitations, organizations such as Rewilding Europe seek to reintroduce the species to its historic range. This study focused on finding suitable reintroduction locations for a population of at least 120 individuals. Through GIS-based multi-criteria decision-making using weighted linear combination and analytical hierarchy process, a model based on known bison habitat preferences, human-centered habitat constraints, and surface geography was used to identify regions large enough to accommodate a new herd. The study area included central-eastern Europe Union countries, specifically Germany, Poland, Lithuania, and Latvia. The model identified several highly suitable regions large enough to support a new herd, with the most optimal located in Poland. Highly suitable areas represented 2.7% of the study region. Relative isolation of suitable regions reinforced the challenges of promoting gene flow between reintroduced European bison herds. This model can be replicated in other conservation planning contexts, including reintroduction of large herbivores considering anthropogenic, ecological, and physical conditions. Numéro de notice : A2020-408 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1672876 Date de publication en ligne : 10/10/2019 En ligne : https://doi.org/10.1080/13658816.2019.1672876 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95467
in International journal of geographical information science IJGIS > vol 34 n° 8 (August 2020) . - pp 1628 - 1647[article]Behavior-based location recommendation on location-based social networks / Seyyed Mohammadreza Rahimi in Geoinformatica, vol 24 n° 3 (July 2020)
[article]
Titre : Behavior-based location recommendation on location-based social networks Type de document : Article/Communication Auteurs : Seyyed Mohammadreza Rahimi, Auteur ; Behrouz Far, Auteur ; Xin Wang, Auteur Année de publication : 2020 Article en page(s) : pp 477 – 504 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] interface web
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] réseau social géodépendant
[Termes IGN] système de recommandationRésumé : (auteur) Location recommendation methods on location-based social networks (LBSN) discover the locational preference of users along with their spatial movement patterns from users’ check-ins and provide users with recommendations of unvisited places. The growing popularity of LBSNs and abundance of shared location information has made location recommendation an active research area in the recent years. However, the existing methods suffer from one or more deficiencies such as data sparsity, cold-start users, ignoring users’ specific spatial and temporal behaviors, not utilizing the shared behaviors of the users. In this paper, we propose a novel location recommendation method, namely Behavior-based Location Recommendation (BLR). BLR recommends a location to a user based on the users’ repetitive behaviors and behaviors of similar users. Additionally, to better integrate the spatial information, BLR has two spatial components, a user-based spatial component to find the spatial preferences of the user, and a behavior-based spatial component to find locations of interest for different behaviors. Experimental studies on three real-world datasets show that BLR produces better location recommendations and can effectively address data sparsity and cold-start problems. Numéro de notice : A2020-370 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-019-00360-3 Date de publication en ligne : 25/05/2019 En ligne : https://doi.org/10.1007/s10707-019-00360-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95265
in Geoinformatica > vol 24 n° 3 (July 2020) . - pp 477 – 504[article]Exploratory bivariate and multivariate geovisualizations of a social vulnerability index / Georgianna Strode in Cartographic perspectives, n° 95 (July 2020)
[article]
Titre : Exploratory bivariate and multivariate geovisualizations of a social vulnerability index Type de document : Article/Communication Auteurs : Georgianna Strode, Auteur ; Victor Mesev, Auteur ; Susanne Bleisch, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse bivariée
[Termes IGN] analyse multivariée
[Termes IGN] analyse spatiale
[Termes IGN] carte thématique
[Termes IGN] données socio-économiques
[Termes IGN] ethnie
[Termes IGN] Floride (Etats-Unis)
[Termes IGN] formule d'Euler
[Termes IGN] planification stratégique
[Termes IGN] prévention
[Termes IGN] santé
[Termes IGN] signe conventionnel
[Termes IGN] sociologie
[Termes IGN] vulnérabilité
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) In the United States, the Centers for Disease Control and Prevention (CDC) is the national agency that conducts and supports public health research and practice. Among the CDC’s many achievements is the development of a social vulnerability index (SVI) to aid planners and emergency responders when identifying vulnerable segments of the population, especially during natural hazard events. The index includes an overall social vulnerability ranking as well as four individual themes: socioeconomic, household composition & disability, ethnicity & language, and housing & transportation. This makes the SVI dataset multivariate, but it is typically viewed via maps that show one theme at a time. This paper explores a suite of cartographic techniques that can represent the SVI beyond the univariate view. Specifically, we recommend three techniques: (1) bivariate mapping to illustrate overall vulnerability and population density, (2) multivariate mapping using cartographic glyphs to disaggregate levels of the four vulnerability themes, and (3) visual analytics using Euler diagrams to depict overlap between the vulnerability themes. The CDC’s SVI, and by extension, vulnerability indices in other countries, can be viewed in a variety of cartographic forms that illustrate the location of vulnerable groups of society. Viewing data from various perspectives can facilitate the understanding and analysis of the growing amount and complexity of data. Numéro de notice : A2020-750 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.14714/CP95.1569 Date de publication en ligne : 17/03/2020 En ligne : https://doi.org/10.14714/CP95.1569 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96404
in Cartographic perspectives > n° 95 (July 2020) . - 19 p.[article]Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases / Meifang Li in Annals of GIS, vol 26 n° 3 (July 2020)
[article]
Titre : Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases Type de document : Article/Communication Auteurs : Meifang Li, Auteur ; Xun Shi, Auteur ; Xia Li, Auteur Année de publication : 2020 Article en page(s) : pp 219 - 226 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] épidémie
[Termes IGN] historique des données
[Termes IGN] modèle orienté objet
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] risque sanitaire
[Termes IGN] système d'information géographique
[Termes IGN] transmissibilitéRésumé : (auteur) In the past several decades, epidemic modelling for communicable diseases has experienced transitions from treating the entire study area as a whole to addressing spatial variation within the area, and from targeting the entire population to incorporating characteristics of categorized subpopulations and finally going down to the individual level. These transitions have been first driven by the recognition that generalizations of space and population in conventional epidemic modelling may have hampered the effectiveness of the modelling; they then have been supported by increasingly available data that allow depiction of detailed spatiotemporal characteristics of an epidemic, as well as those characteristics of the environment in both human and natural aspects; and finally they have been facilitated by developments in geographic information science, data science, computer science, and computing technologies. Based on a review of a variety of recently developed communicable disease models, we explicitly put forward the notions of spatialization and individualization in this area, and point out that the integration of the two is the future of communicable disease modelling. We also point out that in this area models based on the object conceptualization are good at modelling spatiotemporal process, whereas models based on the field conceptualization are good at representing spatialized information. We propose a procedural framework of epidemic modelling that implements the integration of individualization and spatialization, integration of object-based process and field-based representation, and integration of modelling that retrospectively traces infection relationships based on historical patient data and modelling that prospectively predicts such relationships of future epidemics. Numéro de notice : A2020-581 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1768438 Date de publication en ligne : 25/05/2020 En ligne : https://doi.org/10.1080/19475683.2020.1768438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95903
in Annals of GIS > vol 26 n° 3 (July 2020) . - pp 219 - 226[article]Micro diagrams: visualization of categorical point data from location-based social media / Mathias Gröbe in Cartography and Geographic Information Science, Vol 47 n° 4 (July 2020)
[article]
Titre : Micro diagrams: visualization of categorical point data from location-based social media Type de document : Article/Communication Auteurs : Mathias Gröbe, Auteur ; Dirk Burghardt, Auteur Année de publication : 2020 Article en page(s) : pp 305-320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatiale
[Termes IGN] diagramme
[Termes IGN] données localisées des bénévoles
[Termes IGN] réseau social
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Location-based social media data from different platforms such as Twitter and Flickr increasingly serve with their point-geocoded content as data sources for a variety of applications. The standard visualization method uses a derivation of point maps, which works well with a limited amount of data, but it suffers from weaknesses related to cluttering and overlapping, especially for sets of categories. We developed a new visualization method for categorical point data, called “Micro Diagrams”, which uses small diagrams to show the percentages of categories and the spatial distribution. The processing steps to derive the micro diagrams start with aggregating the points in a regular grid structure, which is followed by the selection of the diagram type that represents the numerical proportions and the application of a size scaling function to show the amounts of data. Various parameterization options are discussed and the influence of the color selection is analyzed. Finally, a case study combined with a user test presents the strengths and limits of the micro diagram method. Numéro de notice : A2020-189 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1733438 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.1080/15230406.2020.1733438 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95154
in Cartography and Geographic Information Science > Vol 47 n° 4 (July 2020) . - pp 305-320[article]Réservation
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