Descripteur
Documents disponibles dans cette catégorie (297)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
The socio-environmental data explorer (SEDE) : a social media–enhanced decision support system to explore risk perception to hazard events / Eric Shook in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)
[article]
Titre : The socio-environmental data explorer (SEDE) : a social media–enhanced decision support system to explore risk perception to hazard events Type de document : Article/Communication Auteurs : Eric Shook, Auteur ; Victoria K. Turner, Auteur Année de publication : 2016 Article en page(s) : pp 427 - 441 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de données
[Termes IGN] données environnementales
[Termes IGN] Etats-Unis
[Termes IGN] exploration de données
[Termes IGN] neige
[Termes IGN] outil d'aide à la décision
[Termes IGN] perception
[Termes IGN] réseau social
[Termes IGN] risque environnemental
[Termes IGN] risque technologique
[Termes IGN] tempête
[Termes IGN] temps réelRésumé : (Auteur) Social media are increasingly recognized as a useful data source for understanding social response to hazard events in real time and in post-event analysis. This article establishes social media–enhanced decision support systems (SME-DSS) as a synergistic integration of social media and decision support systems (DSSs) to provide structured access to native, near real-time data from a large and diverse population to assess social response to social, environmental, and technological risk and hazard events. We introduce a prototype SME-DSS entitled socio-environmental data explorer (SEDE) to explore the opportunities and challenges of leveraging social media for decision support. We use a winter storm during 25–28 January 2015 that accumulated record amounts of snow along the East Coast of the United States as a case study to evaluate SEDE in helping assess social response to environmental risk and hazard events as well as evaluate social media as a theoretical component within the social amplification of risk framework (SARF) that serves as a theoretical foundation for SME-DSS. Numéro de notice : A2016-693 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2015.1131627 En ligne : https://doi.org/10.1080/15230406.2015.1131627 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82030
in Cartography and Geographic Information Science > vol 43 n° 5 (November 2016) . - pp 427 - 441[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Mining spatiotemporal co-occurrence patterns in non-relational databases / Berkay Aydin in Geoinformatica, vol 20 n° 4 (October - December 2016)
[article]
Titre : Mining spatiotemporal co-occurrence patterns in non-relational databases Type de document : Article/Communication Auteurs : Berkay Aydin, Auteur ; Vijay Akkineni, Auteur ; Rafal Angryk, Auteur Année de publication : 2016 Article en page(s) : pp 801 - 828 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données répartie
[Termes IGN] données spatiotemporelles
[Termes IGN] exploration de données géographiquesRésumé : (Auteur) Spatiotemporal co-occurrence patterns (STCOPs) represent the subsets of feature types whose instances are frequently co-occurring both in space and time. Spatiotemporal co-occurrences reflect the spatiotemporal overlap relationships among two or more spatiotemporal instances both in spatial and temporal dimensions. STCOPs can be potentially used to predict and understand the generation and evolution of different types of interacting phenomena in various scientific fields such as astronomy, meteorology, biology, geosciences. Meaningful and statistically significant data analysis for these scientific fields requires processing sufficiently large datasets. Due to the computationally expensive nature of spatiotemporal operations required for mining spatiotemporal co-occurrences, it is increasingly difficult to identify spatiotemporal co-occurrences and discover STCOPs in centralized system settings. As a solution, we developed a cloud-based distributed mining system for discovering STCOPs. Our system uses Accumulo, a column-oriented non-relational database management system as its backbone. In order to efficiently mine the STCOPs, we propose three data models for managing trajectory-based spatiotemporal data in Accumulo. We introduce an in-memory join-index structure and a join algorithm for effectively performing spatiotemporal join operations on spatiotemporal trajectories in non-relational databases. Lastly, with the experiments with artificial and real life datasets, we evaluate the performance of the proposed models for STCOP mining. Numéro de notice : A2016-816 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0255-0 En ligne : http://dx.doi.org/10.1007/s10707-016-0255-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82618
in Geoinformatica > vol 20 n° 4 (October - December 2016) . - pp 801 - 828[article]On discovering co-location patterns in datasets : a case study of pollutants and child cancers / Jundong Li in Geoinformatica, vol 20 n° 4 (October - December 2016)
[article]
Titre : On discovering co-location patterns in datasets : a case study of pollutants and child cancers Type de document : Article/Communication Auteurs : Jundong Li, Auteur ; Aibek Adilmagambetov, Auteur ; Mohomed Shazan Mohomed Jabbar, Auteur Année de publication : 2016 Article en page(s) : pp 651 - 692 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] algorithme de tri
[Termes IGN] analyse spatiale
[Termes IGN] co-positionnement
[Termes IGN] enfant
[Termes IGN] exploration de données géographiques
[Termes IGN] polluant
[Termes IGN] santé
[Termes IGN] test statistiqueRésumé : (Auteur) We intend to identify relationships between cancer cases and pollutant emissions by proposing a novel co-location mining algorithm. In this context, we specifically attempt to understand whether there is a relationship between the location of a child diagnosed with cancer with any chemical combinations emitted from various facilities in that particular location. Co-location pattern mining intends to detect sets of spatial features frequently located in close proximity to each other. Most of the previous works in this domain are based on transaction-free apriori-like algorithms which are dependent on user-defined thresholds, and are designed for boolean data points. Due to the absence of a clear notion of transactions, it is nontrivial to use association rule mining techniques to tackle the co-location mining problem. Our proposed approach is focused on a grid based transactionization? of the geographic space, and is designed to mine datasets with extended spatial objects. It is also capable of incorporating uncertainty of the existence of features to model real world scenarios more accurately. We eliminate the necessity of using a global threshold by introducing a statistical test to validate the significance of candidate co-location patterns and rules. Experiments on both synthetic and real datasets reveal that our algorithm can detect a considerable amount of statistically significant co-location patterns. In addition, we explain the data modelling framework which is used on real datasets of pollutants (PRTR/NPRI) and childhood cancer cases. Numéro de notice : A2016-813 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0254-1 En ligne : http://dx.doi.org/10.1007/s10707-016-0254-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82614
in Geoinformatica > vol 20 n° 4 (October - December 2016) . - pp 651 - 692[article]Modeling spatiotemporal information generation / Simon Scheider in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
[article]
Titre : Modeling spatiotemporal information generation Type de document : Article/Communication Auteurs : Simon Scheider, Auteur ; Benedikt Gräler, Auteur ; Edzer J. Pebesma, Auteur ; Christophe Stasch, Auteur Année de publication : 2016 Article en page(s) : pp 1980 - 2008 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données dérivée
[Termes IGN] données hétérogènes
[Termes IGN] exploration de données géographiques
[Termes IGN] information géographique
[Termes IGN] mise à jour de base de données
[Termes IGN] mise à jour en continu
[Termes IGN] regroupement de données
[Termes IGN] source de donnéesRésumé : (Auteur) Maintaining knowledge about the provenance of datasets, that is, about how they were obtained, is crucial for their further use. Contrary to what the overused metaphors of ‘data mining’ and ‘big data’ are implying, it is hardly possible to use data in a meaningful way if information about sources and types of conversions is discarded in the process of data gathering. A generative model of spatiotemporal information could not only help automating the description of derivation processes but also assessing the scope of a dataset’s future use by exploring possible transformations. Even though there are technical approaches to document data provenance, models for describing how spatiotemporal data are generated are still missing. To fill this gap, we introduce an algebra that models data generation and describes how datasets are derived, in terms of types of reference systems. We illustrate its versatility by applying it to a number of derivation scenarios, ranging from field aggregation to trajectory generation, and discuss its potential for retrieval, analysis support systems, as well as for assessing the space of meaningful computations. Numéro de notice : A2016-573 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1151520 En ligne : http://dx.doi.org/10.1080/13658816.2016.1151520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81729
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1980 - 2008[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Unsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning / Jari Vauhkonen in Forestry, an international journal of forest research, vol 89 n° 4 (August 2016)
[article]
Titre : Unsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur ; Joni Imponen, Auteur Année de publication : 2016 Article en page(s) : pp 350 - 363 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Aves
[Termes IGN] biodiversité végétale
[Termes IGN] classification non dirigée
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] exploration de données géographiques
[Termes IGN] gestion de la vie sauvage
[Termes IGN] gestion forestière durable
[Termes IGN] habitat d'espèce
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) To account for ecological objectives in forest management planning, potential habitats need to be mapped, characterized and evaluated for utility in alternative management practices. Airborne laser scanning (ALS) is increasingly used to derive predictive maps of habitat quality. Unlike ecologically driven approaches that require spatially and temporally co-located training data of the specific species, we tested whether indicative information on the habitat potential could be obtained by means of an unsupervised classification of ALS data. Based on a literature review, altogether five ALS features quantifying vegetation height, cover and diversity were expected to capture the essential variation in the habitat requirements of western capercaillie (Tetrao urogallus L.) and hazel grouse (Tetrastes bonasia L.), which are the most important game birds occurring in the studied area. The features were extracted from sparse density, leaf-off ALS data at a resolution of 256 m2 and partitioned using an unsupervised k-means algorithm. By analysing the persistence of the cluster ensemble formed by the partitioning, altogether 158 plots in 16 structural classes were assigned for field measurements to determine which real-world forest phenomena affected the clustering. The clustering was found to stratify the area mainly in terms of size-related attributes such as timber volume and basal area. The understorey, shrub and herb layers had less correspondence with the clustering, indicating that an unsupervised classification is not directly suitable for habitat mapping. The result was improved using empirical threshold values for the ALS features determined according to the plots labelled as the most potential habitats in the field measurements. This semi-supervised classification of the data indicated 4 per cent of the total forest area as suitable for the specific species, which appears a reasonable estimate of the core area of the habitats considered. Overall, the partitioning formed aggregated, stand-like spatial patterns, even though the neighbourhoods of the individual 256 m2 cells were not considered at all. The result could be further refined by spatial optimization to produce indicative maps for forest management planning with ALS as the sole data source. Numéro de notice : A2016--155 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpw011 En ligne : https://doi.org/10.1093/forestry/cpw011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85780
in Forestry, an international journal of forest research > vol 89 n° 4 (August 2016) . - pp 350 - 363[article]Enabling maps/location searches on mobile devices: constructing a POI database via focused crawling and information extraction / Hsiu-Min Chuang in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)PermalinkA hierarchical approach to three-dimensional segmentation of LiDAR data at single-tree level in a multilayered forest / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkThe story of DB4GeO – A service-based geo-database architecture to support multi-dimensional data analysis and visualization / Martin Breunig in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)PermalinkUsing seal trajectories in biological early warning system for real-time zone tracking / Rouaa Wannous in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 21 n° 4 (juillet - août 2016)PermalinkGrid pattern recognition in road networks using the C4.5 algorithm / Jing Tian in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)PermalinkAnalysis of human mobility patterns from GPS trajectories and contextual information / Katarzyna Siła-Nowicka in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkA new method for discovering behavior patterns among animal movements / Yuwei Wang in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkOnline interactive thematic mapping: Applications and techniques for socio-economic research / Duncan A. Smith in Computers, Environment and Urban Systems, vol 57 (May 2016)PermalinkExploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper) / Ran Wang in Geoinformatica, vol 20 n° 2 (April - June 2016)PermalinkIntegrating geo web services for a user driven exploratory analysis / Simon Moncrieff in ISPRS Journal of photogrammetry and remote sensing, vol 114 (April 2016)Permalink