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Mining spatiotemporal association patterns from complex geographic phenomena / Zhanjun He in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 6 (June 2020) . - pp 1162 -1 187 Titre : Mining spatiotemporal association patterns from complex geographic phenomena Type de document : Article/Communication Auteurs : Zhanjun He, Auteur ; Jiannan Cai, Auteur ; Zhong Xie, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1162 -1 187 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] approche hiérarchique [Termes IGN] Chine [Termes IGN] diffusion spatiale [Termes IGN] données localisées dynamiques [Termes IGN] exploration de données géographiques [Termes IGN] interaction spatiale [Termes IGN] modèle entité-association [Termes IGN] modélisation spatio-temporelle [Termes IGN] phénomène géographique [Termes IGN] pollution atmosphérique [Termes IGN] tempête Résumé : (auteur) Spatiotemporal association pattern mining can discover interesting interdependent relationships among various types of geospatial data. However, existing mining methods for spatiotemporal association patterns usually model geographic phenomena as simple spatiotemporal point events. Therefore, they cannot be applied to complex geographic phenomena, which continuously change their properties, shapes or locations, such as storms and air pollution. The most salient feature of such complex geographic phenomena is the geographic dynamic. To fully reveal dynamic characteristics of complex geographic phenomena and discover their associated factors, this research proposes a novel complex event-based spatiotemporal association pattern mining framework. First, a complex geographic event was hierarchically modeled and represented by a new data structure named directed spatiotemporal routes. Then, sequence mining technique was applied to discover the spatiotemporal spread pattern of the complex geographic events. An adaptive spatiotemporal episode pattern mining algorithm was proposed to discover the candidate driving factors for the occurrence of complex geographic events. Finally, the proposed approach was evaluated by analyzing the air pollution in the region of Beijing-Tianjin-Hebei. The experimental results showed that the proposed approach can well address the geographic dynamic of complex geographic phenomena, such as the spatial spreading pattern and spatiotemporal interaction with candidate driving factors. Numéro de notice : A2020-340 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1566549 Date de publication en ligne : 01/02/2019 En ligne : https://doi.org/10.1080/13658816.2019.1566549 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95216 [article]

A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data / Haiyan Tao in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 3 (March 2020) . - pp 604 - 624 Titre : A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data Type de document : Article/Communication Auteurs : Haiyan Tao, Auteur ; Keli Wang, Auteur ; Li Zhuo, Auteur Année de publication : 2020 Article en page(s) : pp 604 - 624 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] Chine [Termes IGN] diffusion spatiale [Termes IGN] distribution de Poisson [Termes IGN] données socio-économiques [Termes IGN] hétérogénéité environnementale [Termes IGN] hétérogénéité spatiale [Termes IGN] maladie infectieuse [Termes IGN] migration humaine [Termes IGN] mobilité territoriale [Termes IGN] modèle de régression [Termes IGN] modèle mathématique [Termes IGN] origine - destination [Termes IGN] point d'intérêt [Termes IGN] risque sanitaire [Termes IGN] urbanisation Résumé : (auteur) International communication and global cooperation have greatly accelerated the worldwide spread of dengue fever, increasing the impact of imported cases on dengue outbreaks in non-naturally endemic areas. Existing studies mostly focus on describing the quantitative relationship between imported cases and local transmission but ignore the space-time diffusion mode of imported cases under the influence of individual mobility. In this paper, we propose a comprehensive framework at a fine scale to establish the disease transmission network and a mathematical model, which constructs ‘source-sink’ links between the imported and indigenous cases on a regular grid with a spatial resolution of 1 km to explore the diffusion pattern and spatiotemporal heterogeneity of imported cases. An application to Guangzhou, China, reveals the main flow and transmission path of imported cases under the influence of human movement and identifies the spatiotemporal distribution of transmission speed according to the time lag of each source-sink link. In addition, we demonstrate that using individual-based movement data and socio-economic factors to study human mobility and imported cases can help to understand the driving forces of dengue spread. Our research provides a comprehensive framework for the analysis of early dengue transmission patterns with benefits to similar urban applications. Numéro de notice : A2020-107 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684497 Date de publication en ligne : 18/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684497 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94707 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2020031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Spatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods / Wolfgang B. Hamer in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)  

Public [article]  inISPRS International journal of geo-information > Vol 9 n° 1 (January 2020) Titre : Spatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods Type de document : Article/Communication Auteurs : Wolfgang B. Hamer, Auteur ; Tim Birr, Auteur ; Joseph-Alexander Verreet, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Allemagne [Termes IGN] apprentissage automatique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] diffusion spatiale [Termes IGN] données localisées [Termes IGN] données météorologiques [Termes IGN] géostatistique [Termes IGN] maladie phytosanitaire [Termes IGN] modèle de simulation [Termes IGN] modèle dynamique [Termes IGN] rendement agricole [Termes IGN] risque environnemental [Termes IGN] temps réel Résumé : (auteur) Real-time identification of the occurrence of dangerous pathogens is of crucial importance for the rapid execution of countermeasures. For this purpose, spatial and temporal predictions of the spread of such pathogens are indispensable. The R package papros developed by the authors offers an environment in which both spatial and temporal predictions can be made, based on local data using various deterministic, geostatistical regionalisation, and machine learning methods. The approach is presented using the example of a crops infection by fungal pathogens, which can substantially reduce the yield if not treated in good time. The situation is made more difficult by the fact that it is particularly difficult to predict the behaviour of wind-dispersed pathogens, such as powdery mildew (Blumeria graminis f. sp. tritici). To forecast pathogen development and spatial dispersal, a modelling process scheme was developed using the aforementioned R package, which combines regionalisation and machine learning techniques. It enables the prediction of the probability of yield- relevant infestation events for an entire federal state in northern Germany at a daily time scale. To run the models, weather and climate information are required, as is knowledge of the pathogen biology. Once fitted to the pathogen, only weather and climate information are necessary to predict such events, with an overall accuracy of 68% in the case of powdery mildew at a regional scale. Thereby, 91% of the observed powdery mildew events are predicted Numéro de notice : A2020-116 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9010044 Date de publication en ligne : 15/01/2020 En ligne : https://doi.org/10.3390/ijgi9010044 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94723 [article]

Hyperspectral image classification based on three-dimensional scattering wavelet transform / Yuan Yan Tang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 5 (mai 2015) . - pp 2467 - 2480 Titre : Hyperspectral image classification based on three-dimensional scattering wavelet transform Type de document : Article/Communication Auteurs : Yuan Yan Tang, Auteur ; Y. Lu, Auteur ; Haoliang Yuan, Auteur Année de publication : 2015 Article en page(s) : pp 2467 - 2480 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] classification spectrale [Termes IGN] diffusion spatiale [Termes IGN] filtrage numérique d'image [Termes IGN] image hyperspectrale [Termes IGN] transformation en ondelettes Résumé : (Auteur) Recent research has shown that utilizing the spectral-spatial information can improve the performance of hyperspectral image (HSI) classification. Since HSI is a 3-D cube datum, 3-D spatial filtering becomes a simple and effective method for extracting the spectral-spatial information. In this paper, we propose a 3-D scattering wavelet transform, which filters the HSI cube data with a cascade of wavelet decompositions, complex modulus, and local weighted averaging. The scattering feature can adequately capture the spectral-spatial information for classification. In the classification step, a support vector machine based on Gaussian kernel is used as a classifier due to its capability to deal with high-dimensional data. Our method is fully evaluated on four classic HSIs, i.e., Indian Pines, Pavia University, Botswana, and Kennedy Space Center. The classification results show that our method achieves as high as 94.46%, 99.30%, 97.57%, and 95.20% accuracies, respectively, when only 5% of the total samples per class is labeled. Numéro de notice : A2015-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2360672 En ligne : https://doi.org/10.1109/TGRS.2014.2360672 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77524 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2015051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Spatial approaches to modeling dispersion of communicable diseases : A review / L. Bian in Transactions in GIS, vol 17 n° 1 (February 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 1 (February 2013) . - pp 1 - 17 Titre : Spatial approaches to modeling dispersion of communicable diseases : A review Type de document : Article/Communication Auteurs : L. Bian, Auteur Année de publication : 2013 Article en page(s) : pp 1 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse comparative [Termes IGN] diffusion spatiale [Termes IGN] données spatiotemporelles [Termes IGN] épidémie [Termes IGN] modèle de dispersion [Termes IGN] processus spatial [Termes IGN] processus temporel [Termes IGN] système d'information géographique Résumé : (Auteur) The dispersion of communicable diseases in a population is intrinsically spatial. In the last several decades, a range of spatial approaches has been devised to model epidemiological processes; and they differ significantly from each other. A review of spatially oriented epidemiological models is necessary to assess advances in spatial approaches to modeling disease dispersion and to help identify those most appropriate for specific research goals. The most notable difference in the design of these spatially oriented models is the scale and mobility of the modeling unit. Using two criteria, this review identifies six types of spatially oriented models. These include: (1) population-based wave models, (2) sub-population models, (3) individual-based cellular automata models, (4) mobile sub-population models, (5) individual-based spatially implicit models, and (6) individual-based mobile models. Each model type is evaluated in terms of its design principles, assumptions, and intended applications. For the evaluation of design, four aspects of design principles are discussed: the modeling unit, the interaction between the modeling units, the spatial process, and the temporal process utilized in a design. Insights gained from this review can be useful for devising much-needed spatially and temporally oriented strategies to forecast, prevent, and control communicable diseases. Numéro de notice : A2013-037 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01329.x Date de publication en ligne : 23/07/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01329.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32175 [article]

Modélisation des changements d’occupation et d’utilisation du sol: Cadres formels et exemple d’application / M. Theriault in Revue internationale de géomatique, vol 21 n° 3 (septembre - novembre 2011)  

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Diffusion automatique des déformations géométriques sur des objets linéaires et surfaciques / Cristel Legrand (2004)

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Modèles en analyse spatiale / Léna Sanders (2001)

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Accessibilité et diffusion spatiale / Pierre Dumolard in Espace géographique, vol 28 n° 3 (octobre - décembre 1999)  

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La diffusion spatiale des technologies de l'information géographique en France / Stéphane Roche in Mappemonde, vol 1999 n° 1 tome 53 (mars 1999)  

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L'analyse spatiale en géographie humaine / P. Haggett (1973)

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