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HV-LSC-ex2 : velocity field interpolation using extended least-squares collocation / Rebekka Steffen in Journal of geodesy, vol 96 n° 3 (March 2022)
[article]
Titre : HV-LSC-ex2 : velocity field interpolation using extended least-squares collocation Type de document : Article/Communication Auteurs : Rebekka Steffen, Auteur ; Juliette Legrand, Auteur ; Jonas Ågren, Auteur ; Holger Steffen, Auteur ; M. Lidberg, Auteur Année de publication : 2022 Article en page(s) : n° 15 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] champ de vitesse
[Termes IGN] collocation par moindres carrés
[Termes IGN] interpolation
[Termes IGN] modèle mathématiqueRésumé : (auteur) Least-squares collocation (LSC) is a widely used method applied in physical geodesy to separate observations into a signal and noise part but has received only little attention when interpolating velocity fields. The advantage of the LSC is the possibility to filter and interpolate as well as extrapolate the observations. Here, we will present several extensions to the traditional LSC technique, which allows the combined interpolation of both horizontal velocity components (horizontal velocity (HV)-LSC), the separation of velocity observations on different tectonic plates, and the removal of stationarity by moving variance (the latter as HV-LSC-ex(tended)2). Furthermore, the covariance analysis, which is required to find necessary input parameters for the LSC, is extended by finding a suitable variance and correlation length using both horizontal velocity components at the same time. The traditional LSC and all extensions are tested on a synthetic dataset to find the signal at known as well as newly defined points, with stations separated on four different plates with distinct plate velocities. The methodologies are evaluated by calculation of a misfit to the input data, and implementation of a leave-one-out cross-validation and a Jackknife resampling. The largest improvement in terms of reduced misfit and stability of the interpolation can be obtained when plate boundaries are considered. In addition, any small-scale changes can be filtered out using the moving-variance approach and a smoother velocity field is obtained. In comparison with interpolation using the Kriging method, the fit is better using the new HV-LSC-ex2 technique. Numéro de notice : A2022-151 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1007/s00190-022-01601-4 Date de publication en ligne : 04/03/2022 En ligne : http://dx.doi.org/10.1007/s00190-022-01601-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100111
in Journal of geodesy > vol 96 n° 3 (March 2022) . - n° 15[article]Early warning of COVID-19 hotspots using human mobility and web search query data / Takahiro Yabe in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Early warning of COVID-19 hotspots using human mobility and web search query data Type de document : Article/Communication Auteurs : Takahiro Yabe, Auteur ; Kota Tsubouchi, Auteur ; Yoshihide Sekimoto, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101747 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aide à la localisation
[Termes IGN] analyse de données
[Termes IGN] analyse de groupement
[Termes IGN] épidémie
[Termes IGN] exploration de données
[Termes IGN] maladie virale
[Termes IGN] mobilité urbaine
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] requête spatiale
[Termes IGN] ressources web
[Termes IGN] surveillance sanitaire
[Termes IGN] Tokyo (Japon)Résumé : (auteur) COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies have shown the effectiveness of using large-scale mobility data to monitor the impacts of non-pharmaceutical interventions (e.g., lockdowns) through population density analysis. However, predicting the locations of potential outbreak occurrence is difficult using mobility data alone. Meanwhile, web search queries have been shown to be good predictors of the disease spread. In this study, we utilize a unique dataset of human mobility trajectories (GPS traces) and web search queries with common user identifiers (> 450 K users), to predict COVID-19 hotspot locations beforehand. More specifically, web search query analysis is conducted to identify users with high risk of COVID-19 contraction, and social contact analysis was further performed on the mobility patterns of these users to quantify the risk of an outbreak. Our approach is empirically tested using data collected from users in Tokyo, Japan. We show that by integrating COVID-19 related web search query analytics with social contact networks, we are able to predict COVID-19 hotspot locations 1–2 weeks beforehand, compared to just using social contact indexes or web search data analysis. This study proposes a novel method that can be used in early warning systems for disease outbreak hotspots, which can assist government agencies to prepare effective strategies to prevent further disease spread. Human mobility data and web search query data linked with common IDs are used to predict COVID-19 outbreaks. High risk social contact index captures both the contact density and COVID-19 contraction risks of individuals. Real world data was collected from 200 K individual users in Tokyo during the COVID-19 pandemic. Experiments showed that the index can be used for microscopic outbreak early warning. Numéro de notice : A2022-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101747 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101747 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99637
in Computers, Environment and Urban Systems > vol 92 (March 2022) . - n° 101747[article]Evaluation of the mixed-effects model and quantile regression approaches for predicting tree height in larch (Larix olgensis) plantations in northeastern China / Longfei Xie in Canadian Journal of Forest Research, Vol 52 n° 3 (March 2022)
[article]
Titre : Evaluation of the mixed-effects model and quantile regression approaches for predicting tree height in larch (Larix olgensis) plantations in northeastern China Type de document : Article/Communication Auteurs : Longfei Xie, Auteur ; Faris Rafi Almay Widagdo, Auteur ; Zheng Miao, Auteur ; Lihu Dong, Auteur ; Fengri Li, Auteur Année de publication : 2022 Article en page(s) : pp 309 - 319 Note générale : bibliographie Langues : Français (fre) Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] biométrie
[Termes IGN] Chine
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] hauteur des arbres
[Termes IGN] Larix olgensis
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] régression non linéaire
[Termes IGN] régression par quantileRésumé : (auteur) Tree height (H) is one of the most important tree variables and is widely used in growth and yield models, and its measurement is often time-consuming and costly. Hence, height–diameter (H–D) models have become a great alternative, providing easy-to-use and accurate tools for H prediction. In this study, H–D models were developed for Larix olgensis A. Henry in northeastern China. The Chapman–Richards function with three predictors (diameter at breast height, dominant tree height, and relative size of individual trees) performed best. Nonlinear mixed-effects (NLME) models and nonlinear quantile regressions (NQR9, nine quantiles; NQR5, five quantiles; and NQR3, three quantiles) were further used and improved the generalized H–D model, successfully providing accurate H predictions. In addition, the H predictions were calibrated using several measurements from subsamples, which were obtained from different sampling designs and sizes. The results indicated that the predictive accuracy was higher when calibrated by using any number of height measurements for the NLME model and more than three height measurements for the NQR3, NQR5, and NQR9 models. The best sampling strategy for the NLME and NQR models involved sampling medium-sized trees. Overall, the newly developed H–D models can provide highly accurate height predictions for L. olgensis. Numéro de notice : A2022-313 Affiliation des auteurs : non IGN Autre URL associée : Draft Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1139/cjfr-2021-0184 En ligne : https://doi.org/10.1139/cjfr-2021-0184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100412
in Canadian Journal of Forest Research > Vol 52 n° 3 (March 2022) . - pp 309 - 319[article]A search step optimization in an ambiguity function-based GNSS precise positioning / Sławomir Cellmer in Survey review, vol 54 n° 383 (March 2022)
[article]
Titre : A search step optimization in an ambiguity function-based GNSS precise positioning Type de document : Article/Communication Auteurs : Sławomir Cellmer, Auteur ; Krzysztof Nowel, Auteur ; Artur Fischer, Auteur Année de publication : 2022 Article en page(s) : pp 117 - 124 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] ambiguïté entière
[Termes IGN] diagramme de Voronoï
[Termes IGN] modèle mathématique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] positionnement par GNSS
[Termes IGN] précision du positionnementRésumé : (auteur) The search procedure, as a part of the Modified Ambiguity Function Approach (MAFA), is conducted in the coordinate space. The main advantage of searching for a fixed solution in the coordinate domain, instead of in the ambiguity domain, is the constant search space dimension, which amounts to three. In contrast, an ambiguity space dimension can presently achieve over twenty when the positioning is based on multi-system data. Thus, in the MAFA method, the computational complexity is independent of the number of satellites. We propose a new method of estimating the length of the search step. In this method, the actual satellite configuration determines the size of the search step. Therefore, the data-driven search step is always optimal, regardless of the current satellite configuration. The mathematical model of the new approach is provided together with a detailed algorithm. The numerical experiment follows the description of the search procedure. Numéro de notice : A2022-239 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2021.1885947 Date de publication en ligne : 17/02/2021 En ligne : https://doi.org/10.1080/00396265.2021.1885947 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100163
in Survey review > vol 54 n° 383 (March 2022) . - pp 117 - 124[article]Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea / Yang Xu in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea Type de document : Article/Communication Auteurs : Yang Xu, Auteur ; Dan Zou, Auteur ; Sangwon Park, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] chaîne de Markov
[Termes IGN] classification par réseau neuronal récurrent
[Termes IGN] Corée du sud
[Termes IGN] durée de trajet
[Termes IGN] mobilité humaine
[Termes IGN] modèle de simulation
[Termes IGN] prévision à court terme
[Termes IGN] téléphone intelligent
[Termes IGN] téléphonie mobile
[Termes IGN] tourisme
[Termes IGN] voyageRésumé : (auteur) The abilities to predict tourist movements are critical to many urban applications, such as travel recommendations, targeted advertising, and infrastructure planning. Despite its importance, our understanding on the movement predictability of urban tourists and visitors is still limited, partially due to difficulties in accessing large scale mobility observations. In this study, we aim to bridge this gap by analyzing a nationwide mobile phone dataset. The dataset captures movement traces of a large number of international travelers who visited South Korea in 2018. By introducing two prediction models, one being Markov chain and the other with a recurrent neural network architecture, we assess how well travelers’ movements can be predicted under different model settings, and examine how predictability relates to travelers’ length of stay and activeness in travel patterns. Since travelers’ destination choices are quite diverse in South Korea, this enables us to further investigate the geographic variation of the models’ performance. Results show that the Markov chain model achieves an overall accuracy between 33.4% (@Acc1 metric) and 64.2% (@Acc5 metric), compared to 41.9% (@Acc1) and 67.7% (@Acc5) for the recurrent neural network model. The prediction capabilities of both models are largely unequal across individuals, with active travelers being more predictable in general. There is a notable geographic variation in the models’ performance, meaning that travelers’ movements are more predictable in some cities, but less in others. We believe this study represents a new effort in portraying the movement predictability of urban tourists and visitors. The analytical framework can be applied to assist tourism planning and service deployment in cities. Numéro de notice : A2022-085 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101753 Date de publication en ligne : 06/01/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99490
in Computers, Environment and Urban Systems > vol 92 (March 2022)[article]Suspended sediment prediction using integrative soft computing models: on the analogy between the butterfly optimization and genetic algorithms / Marzieh Fadaee in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkAn integrated framework of global sensitivity analysis and calibration for spatially explicit agent-based models / Jeon-Young Kang in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkDevelopment of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan / Eunbeen Park in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkExploring the advantages of the maximum entropy model in calibrating cellular automata for urban growth simulation: a comparative study of four methods / Bin Zhang in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkMapping abundance distributions of allergenic tree species in urbanized landscapes: A nation-wide study for Belgium using forest inventory and citizen science data / Sébastien Dujardin in Landscape and Urban Planning, vol 218 (February 2022)PermalinkNovel model for predicting individuals’ movements in dynamic regions of interest / Xiaoqi Shen in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkRaw GIS to 3D road modeling for real-time traffic simulation / Yacine Amara in The Visual Computer, vol 38 n° 1 (January 2022)PermalinkAn extended patch-based cellular automaton to simulate horizontal and vertical urban growth under the shared socioeconomic pathways / Yimin Chen in Computers, Environment and Urban Systems, vol 91 (January 2022)PermalinkClassification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkCombining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China / Huijuan Zhang in Computers & geosciences, vol 158 (January 2022)Permalink