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Termes IGN > ingénierie > systémique > modélisation > modèle dynamique
modèle dynamiqueSynonyme(s)modèle spatiotemporel dynamique |
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Geovisualization of COVID-19: State of the art and opportunities / Yu Lan in Cartographica, vol 56 n° 1 (Spring 2021)
[article]
Titre : Geovisualization of COVID-19: State of the art and opportunities Type de document : Article/Communication Auteurs : Yu Lan, Auteur ; Michael R. Desjardins, Auteur ; Alexander Hohl, Auteur ; Eric Delmelle, Auteur Année de publication : 2021 Article en page(s) : pp 2 - 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement
[Termes IGN] carte interactive
[Termes IGN] carte thématique
[Termes IGN] cube espace-temps
[Termes IGN] données spatiotemporelles
[Termes IGN] Etats-Unis
[Termes IGN] maladie virale
[Termes IGN] modèle dynamique
[Termes IGN] variation saisonnière
[Termes IGN] WebSIG
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Mapping the prevalence and spread of infectious diseases has never been more critical than during the COVID-19 pandemic. A plethora of Web-based GIS dashboards have been created that incorporate basic GIS functionality; these dashboards have served as platforms for rapid data sharing and real-time information, ultimately facilitating decision making. However, many of them have merely focused on presenting and monitoring cumulative or daily incidence of COVID-19 data, disregarding the temporal dimension. In this paper, we review the usefulness of GIS-based dashboards for mapping the prevalence of COVID-19, but also missed opportunities to emphasize the temporal component of the disease (cyclicity, seasonality). We suggest that advanced geovisualization techniques can be used to integrate the temporal component in interactive animated maps illustrating (a) the daily relative risk and the number of days a geographic region has been in a disease cluster, (b) the ratio between the observed and expected number of cases over time, and (c) mortality count dynamics in a space–time cube. We illustrate these approaches by using COVID-19 cases and death counts across the U.S. at the county level from 25 January 2020 to 1 October 2020. We discuss how each of these visualization approaches can promote the understanding of important public health concepts applied to the pandemic such as risk, spread, and mortality. Finally, we suggest future avenues to promote research at the intersection of space–time visualization and infectious diseases. Numéro de notice : A2021-409 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2020-0027 Date de publication en ligne : 15/03/2021 En ligne : https://doi.org/10.3138/cart-2020-0027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97730
in Cartographica > vol 56 n° 1 (Spring 2021) . - pp 2 - 13[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 031-2021011 SL Revue Centre de documentation Revues en salle Disponible Dynamic human body reconstruction and motion tracking with low-cost depth cameras / Kangkan Wang in The Visual Computer, vol 37 n° 3 (March 2021)
[article]
Titre : Dynamic human body reconstruction and motion tracking with low-cost depth cameras Type de document : Article/Communication Auteurs : Kangkan Wang, Auteur ; Guofeng Zhang, Auteur ; Jian Yang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 603 - 618 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de formes
[Termes IGN] déformation de projection
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] filtrage spatiotemporel
[Termes IGN] maillage
[Termes IGN] modèle dynamique
[Termes IGN] modélisation 3D
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'objet
[Termes IGN] squelettisationRésumé : (auteur) We present a novel approach for dynamic human body reconstruction and motion tracking using low-cost depth cameras. Our reconstruction system is able to produce a sequence of dynamic 3D human body models from the noisy input depth data. To accurately align the template model with noisy input data, we combine skeleton-driven deformation and mesh deformation techniques to enhance the registration robustness to depth missing, occlusions, and severe noise. In addition, a novel data-driven 3D human body model is introduced to efficiently reconstruct human body models with wide shape and pose variations only using a limited number of training databases with standard standing pose. We perform quantitative and qualitative experiments to evaluate our method and compare it with other methods for body reconstruction on both synthetic and real datasets. Experimental results demonstrate the effectiveness of the proposed approach. Numéro de notice : A2021-341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01826-4 Date de publication en ligne : 26/02/2020 En ligne : https://doi.org/10.1007/s00371-020-01826-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97579
in The Visual Computer > vol 37 n° 3 (March 2021) . - pp 603 - 618[article]Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach / Bisong Hu in International journal of geographical information science IJGIS, vol 35 n° 3 (March 2021)
[article]
Titre : Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach Type de document : Article/Communication Auteurs : Bisong Hu, Auteur ; Pan Ning, Auteur ; Yi Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 466 - 489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] carte sanitaire
[Termes IGN] Chine
[Termes IGN] entropie maximale
[Termes IGN] filtre de Kalman
[Termes IGN] géostatistique
[Termes IGN] modèle dynamique
[Termes IGN] régressionRésumé : (auteur) In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotemporal mapping purposes, is proposed in a spatiotemporal disease mapping context. The proposed BME-Kalman synthesis allows BME to use information from both parametric regression modeling and KF estimation leading to enhanced knowledge bases. The BME-Kalman synthetic approach is used to study the space-time incidence mapping of the hand, foot and mouth disease (HFMD) in Shandong province (China) during the period May 1st, 2008 to March 19th, 2009. The results showed that the BME-Kalman approach exhibited very good regressive and predictive accuracies, maintained a very good performance even during low-incidence and extremely low-incidence periods, offered an improved description of hierarchical disease characteristics compared to traditional mapping techniques, and provided a clear explanation of the spatial stratified incidence heterogeneity at unsampled locations. The BME-Kalman approach is versatile and flexible so that it can be modified and adjusted according to the needs of the application. Numéro de notice : A2021-165 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1795177 Date de publication en ligne : 22/07/2021 En ligne : https://doi.org/10.1080/13658816.2020.1795177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97098
in International journal of geographical information science IJGIS > vol 35 n° 3 (March 2021) . - pp 466 - 489[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2021031 SL Revue Centre de documentation Revues en salle Disponible A dynamic bidirectional coupled surface flow model for flood inundation simulation / Chunbo Jiang in Natural Hazards and Earth System Sciences, Vol 21 n° 2 (February 2021)
[article]
Titre : A dynamic bidirectional coupled surface flow model for flood inundation simulation Type de document : Article/Communication Auteurs : Chunbo Jiang, Auteur ; Qi Zhou, Auteur ; Wangyang Yu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 497 - 515 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Chine
[Termes IGN] crue
[Termes IGN] inondation
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] modèle hydrographique
[Termes IGN] prévention des risquesRésumé : (auteur) Flood disasters frequently threaten people and property all over the world. Therefore, an effective numerical model is required to predict the impacts of floods. In this study, a dynamic bidirectional coupled hydrologic–hydrodynamic model (DBCM) is developed with the implementation of characteristic wave theory, in which the boundary between these two models can dynamically adapt according to local flow conditions. The proposed model accounts for both mass and momentum transfer on the coupling boundary and was validated via several benchmark tests. The results show that the DBCM can effectively reproduce the process of flood propagation and also account for surface flow interaction between non-inundation and inundation regions. The DBCM was implemented for the floods simulation that occurred at Helin Town located in Chongqing, China, which shows the capability of the model for flood risk early warning and future management. Numéro de notice : A2021-168 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.5194/nhess-21-497-2021 Date de publication en ligne : 03/02/2021 En ligne : https://doi.org/10.5194/nhess-21-497-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97107
in Natural Hazards and Earth System Sciences > Vol 21 n° 2 (February 2021) . - pp 497 - 515[article]Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling / Stefanos Georganos in Geocarto international, vol 36 n° 2 ([01/02/2021])
[article]
Titre : Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling Type de document : Article/Communication Auteurs : Stefanos Georganos, Auteur ; Tais Grippa, Auteur ; Assane Niang Gadiaga, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 121 -1 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] autocorrélation spatiale
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Dakar (Sénégal)
[Termes IGN] densité de population
[Termes IGN] distribution spatiale
[Termes IGN] hétérogénéité spatiale
[Termes IGN] modèle dynamique
[Termes IGN] population
[Termes IGN] utilisation du solRésumé : (auteur) Machine learning algorithms such as Random Forest (RF) are being increasingly applied on traditionally geographical topics such as population estimation. Even though RF is a well performing and generalizable algorithm, the vast majority of its implementations is still ‘aspatial’ and may not address spatial heterogenous processes. At the same time, remote sensing (RS) data which are commonly used to model population can be highly spatially heterogeneous. From this scope, we present a novel geographical implementation of RF, named Geographical Random Forest (GRF) as both a predictive and exploratory tool to model population as a function of RS covariates. GRF is a disaggregation of RF into geographical space in the form of local sub-models. From the first empirical results, we conclude that GRF can be more predictive when an appropriate spatial scale is selected to model the data, with reduced residual autocorrelation and lower Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) values. Finally, and of equal importance, GRF can be used as an effective exploratory tool to visualize the relationship between dependent and independent variables, highlighting interesting local variations and allowing for a better understanding of the processes that may be causing the observed spatial heterogeneity. Numéro de notice : A2021-080 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595177 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96822
in Geocarto international > vol 36 n° 2 [01/02/2021] . - pp 121 -1 36[article]Stand-scale climate change impacts on forests over large areas: transient responses and projection uncertainties / NIca Huber in Ecological Applications, vol 31 ([01/02/2021])PermalinkPermalinkDynamic mechanism of blown sand hazard formation at the Jieqiong section of the Lhasa–Shigatse railway / Shengbo Xie in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)PermalinkSpatiotemporal patterns of urbanization during the last four decades in Switzerland and their impacts on urban heat islands / Marti Bosch Padros (2021)PermalinkBioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates / Robert E. Keane in Forest ecology and management, vol 477 ([01/12/2020])PermalinkSemantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)PermalinkAnalyzing the joint effect of forest management and wildfires on living biomass and carbon stocks in Spanish forests / Patricia Adame in Forests, vol 11 n°11 (November 2020)PermalinkTowards dynamic forest trafficability prediction using open spatial data, hydrological modelling and sensor technology / Aura Salmivaara in Forestry, an international journal of forest research, vol 93 n° 5 (October 2020)PermalinkA spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)PermalinkNear-real time forecasting and change detection for an open ecosystem with complex natural dynamics / Jasper A. Slingsby in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)Permalink