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A probabilistic data model and algebra for location-based data warehouses and their implementation / Igor Timko in Geoinformatica, vol 18 n° 2 (April 2014)
[article]
Titre : A probabilistic data model and algebra for location-based data warehouses and their implementation Type de document : Article/Communication Auteurs : Igor Timko, Auteur ; Curtis Dyreson, Auteur ; Toren Bach Pedersen, Auteur Année de publication : 2014 Article en page(s) : pp 357 - 404 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données localisées
[Termes IGN] entrepôt de données
[Termes IGN] incertitude des données
[Termes IGN] modèle stochastique
[Termes IGN] service fondé sur la position
[Termes IGN] SOLAPRésumé : (Auteur) This paper proposes a novel, probabilistic data model and algebra that improves the modeling and querying of uncertain data in spatial OLAP (SOLAP) to support location-based services. Data warehouses that support location-based services need to combine complex hierarchies, such as road networks or transportation infrastructures, with static and dynamic content, e.g., speed limits and vehicle positions, respectively. Both the hierarchies and the content are often uncertain in real-world applications. Our model supports the use of probability distributions within both facts and dimensions. We give an algebra that correctly aggregates uncertain data over uncertain hierarchies. This paper also describes an implementation of the model and algebra, gives a complexity analysis of the algebra, and reports on an empirical, experimental evaluation of the implementation. The work is motivated with a real-world case study, based on our collaboration with a leading Danish vendor of location-based services. Numéro de notice : A2014-229 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-013-0180-4 Date de publication en ligne : 21/05/2013 En ligne : https://doi.org/10.1007/s10707-013-0180-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33132
in Geoinformatica > vol 18 n° 2 (April 2014) . - pp 357 - 404[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2014021 RAB Revue Centre de documentation En réserve L003 Disponible Using spatial data support for reducing uncertainty in geospatial applications / T. Hong in Geoinformatica, vol 18 n° 1 (January 2014)
[article]
Titre : Using spatial data support for reducing uncertainty in geospatial applications Type de document : Article/Communication Auteurs : T. Hong, Auteur ; K. Hart, Auteur ; Leen-Kiat Soh, Auteur ; Ashok Samal, Auteur Année de publication : 2014 Article en page(s) : pp 63 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] exploration de données géographiques
[Termes IGN] incertitude des données
[Termes IGN] Nebraska (Etats-Unis)
[Termes IGN] série temporelleRésumé : (Auteur) Widespread use of GPS devices and ubiquity of remotely sensed geospatial images along with cheap storage devices have resulted in vast amounts of digital data. More recently, with the advent of wireless technology, a large number of sensor networks have been deployed to monitor many human, biological and natural processes. This poses a challenge in many data rich application domains now: how to best choose the datasets to solve specific problems? In particular, some of the datasets may be redundant and their inclusion in analysis may not only be time consuming, but also lead to erroneous conclusions. On the other hand, excluding some of the datasets hastily might skew the observations drawn. We propose the concept of data support as the basis for efficient, cost-effective and intelligent use of geospatial data in order to reduce uncertainty in the analysis and consequently in the results. Data support is defined as the process of determining the information utility of a data source to help decide which one to include or exclude to improve cost-effectiveness in existing data analysis. In this paper we use mutual information—a concept popular in information theory as a measure to compute information gain or loss between two datasets—as the basis of computing data support. The flexibility and effectiveness of the approach are demonstrated using an application in the hydrological analysis domain, specifically, watersheds in the state of Nebraska. Numéro de notice : A2014-028 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-013-0177-z Date de publication en ligne : 12/06/2013 En ligne : https://doi.org/10.1007/s10707-013-0177-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32933
in Geoinformatica > vol 18 n° 1 (January 2014) . - pp 63 - 92[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval / Jochem Verrlest in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)
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Titre : Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval Type de document : Article/Communication Auteurs : Jochem Verrlest, Auteur ; Juan Pablo Rivera, Auteur ; José Moreno, Auteur ; Gustavo Camps-Valls, Auteur Année de publication : 2013 Article en page(s) : pp 157 - 167 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de Gauss
[Termes IGN] apprentissage automatique
[Termes IGN] chlorophylle
[Termes IGN] image Sentinel-MSI
[Termes IGN] incertitude des données
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] régression
[Termes IGN] surveillance de la végétation
[Termes IGN] teneur en chlorophylle des feuilles
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we focus on a new emerging technique in the field of Bayesian nonparametric modeling. We exploit Gaussian process regression (GPR) for retrieval, which is an accurate method that also provides uncertainty intervals along with the mean estimates. This distinct feature is not shared by other machine learning approaches. In view of implementing the regressor into operational monitoring applications, here the portability of locally trained GPR models was evaluated. Experimental data came from the ESA-led field campaign SPARC (Barrax, Spain). For various simulated S2 configurations (S2-10m, S2-20m and S2-60m) two important biophysical parameters were estimated: leaf chlorophyll content (LCC) and leaf area index (LAI). Local evaluation of an extended training dataset with more variation over bare soil sites led to improved LCC and LAI mapping with reduced uncertainties. GPR reached the 10% precision required by end users, with for LCC a NRMSE of 3.5–9.2% (r2: 0.95–0.99) and for LAI a NRMSE of 6.5–7.3% (r2: 0.95–0.96). The developed GPR models were subsequently applied to simulated Sentinel images over various sites. The associated uncertainty maps proved to be a good indicator for evaluating the robustness of the retrieval performance. The generally low uncertainty intervals over vegetated surfaces suggest that the locally trained GPR models are portable to other sites and conditions. Numéro de notice : A2013-708 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32844
in ISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 157 - 167[article]Using pattern-oriented modeling (POM) to cope with uncertainty in multi-scale agent-based models of land change / Nicholas R. Magliocca in Transactions in GIS, vol 17 n° 6 (December 2013)
[article]
Titre : Using pattern-oriented modeling (POM) to cope with uncertainty in multi-scale agent-based models of land change Type de document : Article/Communication Auteurs : Nicholas R. Magliocca, Auteur ; Erle C. Ellis, Auteur Année de publication : 2013 Article en page(s) : pp 883 - 900 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] aide à la décision
[Termes IGN] changement d'occupation du sol
[Termes IGN] généralisation de base de données
[Termes IGN] incertitude des données
[Termes IGN] occupation du sol
[Termes IGN] représentation multiple
[Termes IGN] système multi-agents
[Termes IGN] utilisation du solRésumé : (Auteur) Local land-use and -cover changes (LUCCs) are the result of both the decisions and actions of individual land-users, and the larger global and regional economic, political, cultural, and environmental contexts in which land-use systems are embedded. However, the dearth of detailed empirical data and knowledge of the influences of global/regional forces on local land-use decisions is a substantial challenge to formulating multi-scale agent-based models (ABMs) of land change. Pattern-oriented modeling (POM) is a means to cope with such process and parameter uncertainty, and to design process-based land change models despite a lack of detailed process knowledge or empirical data. POM was applied to a simplified agent-based model of LUCC to design and test model relationships linking global market influence to agents’ land-use decisions within an example test site. Results demonstrated that evaluating alternative model parameterizations based on their ability to simultaneously reproduce target patterns led to more realistic land-use outcomes. This framework is promising as an agent-based virtual laboratory to test hypotheses of how and under what conditions driving forces of land change differ from a generalized model representation depending on the particular land-use system and location. Numéro de notice : A2013-674 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12012 Date de publication en ligne : 08/01/2013 En ligne : https://doi.org/10.1111/tgis.12012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32810
in Transactions in GIS > vol 17 n° 6 (December 2013) . - pp 883 - 900[article]A random set approach for modeling integrated uncertainties of traffic islands derived from airborne laser scanning points / Liang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 9 (September 2013)
[article]
Titre : A random set approach for modeling integrated uncertainties of traffic islands derived from airborne laser scanning points Type de document : Article/Communication Auteurs : Liang Zhou, Auteur ; Alfred Stein, Auteur Année de publication : 2013 Article en page(s) : pp 835 - 845 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] incertitude des données
[Termes IGN] modèle d'incertitude
[Termes IGN] qualité des données
[Termes IGN] semis de points
[Termes IGN] trafic routierRésumé : (Auteur) Traffic islands play a major role in transport studies by affecting traffic behavior safety, air pollution, and transport decision support. Point data obtained by laser scanning enable the determination of their locations. Planimetric errors, vertical errors, and limited point spacing however affect their spatial data quality (SDQ). In this study, we defined uncertainty as the lack of accuracy and analyzed its importance by modeling each traffic island as a random set. The covering functions of the point data and their intermediate locations were determined by point segmentation, followed by interpolation. In this way, traffic islands were delineated from the background with a transition zone. The study showed that point spacing has the largest contribution to the positonal accuracy of a traffic island. The area of the transition zone has a linear relation with the planimetric errors, whereas the influence of the vertical errors on the accuracy decreases with increasing point spacing. Experiments were conducted to investigate the influences of the parameters in an SDQ analysis. The study demonstrated how different sources of uncertainty can be integrated. Results showed the advantages of using random sets for SDQ modelling. We concluded that modelling of traffic islands by random sets provides meaningful information to integrate uncertainties. Numéro de notice : A2013-506 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.9.835 En ligne : https://doi.org/10.14358/PERS.79.9.835 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32644
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 9 (September 2013) . - pp 835 - 845[article]In-situ transfer standard and coincident-view intercomparisons for sensor cross-calibration / Kurt Thome in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)PermalinkPermalinkPenser le plan archéologique comme un système d'information : L'exemple du site médiéval de Qalhät (Oman) / Olivier Barge in Revue internationale de géomatique, vol 22 n° 3 (septembre - novembre 2012)PermalinkL’anticipation du changement en prospective et des changements spatiaux en géoprospective / Christine Voiron-Canicio in Espace géographique, vol 41 n° 2 (avril - juin 2012)PermalinkLa question de l'efficacité visuelle / Françoise de Blomac in SIG la lettre, n° 129 (septembre 2011)PermalinkApplying time-dependent variance-based global sensitivity analysis to represent the dynamics of an agent-based model of land use change / A. Ligmann-Zielinska in International journal of geographical information science IJGIS, vol 24 n°11-12 (december 2010)PermalinkUncertainty analysis for the classification of multispectral satellite images using SVMs and SOMs / F. Giacco in IEEE Transactions on geoscience and remote sensing, vol 48 n° 10 (October 2010)PermalinkDirected movements in probabilistic time geography / Stephan Winter in International journal of geographical information science IJGIS, vol 24 n° 9 (september 2010)PermalinkPropagating error in land-cover-change analyses: impact of temporal dependence under increased thematic complexity / A. Burnicki in International journal of geographical information science IJGIS, vol 24 n°7-8 (july 2010)PermalinkAccuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 / Nicholas J. Tate (2010)Permalink