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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]Competition and climate influence in the basal area increment models for Mediterranean mixed forests / Diego Rodríguez de Prado in Forest ecology and management, vol 506 (February-15 2022)
[article]
Titre : Competition and climate influence in the basal area increment models for Mediterranean mixed forests Type de document : Article/Communication Auteurs : Diego Rodríguez de Prado, Auteur ; José Riofrio, Auteur ; Jorge Aldea, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 119955 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] climat aride
[Termes IGN] climat méditerranéen
[Termes IGN] croissance des arbres
[Termes IGN] Espagne
[Termes IGN] forêt méditerranéenne
[Termes IGN] gestion forestière durable
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] modélisation de la forêt
[Termes IGN] peuplement mélangé
[Termes IGN] surface terrière
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Competition plays a key role controlling tree growth in mixed forests. Contrary to monocultures, quantifying species mixing influence on tree growth suppose a challenge since the presence of two or more species requires to estimate the degree of intra- and inter-specific competition among trees. Moreover, it is well known that aridity can also influence tree growth, especially in the Mediterranean Basin. In the present context of climate change, it is essential to take into account species mixing and aridity uncertainty in the design of sustainable management guidelines for Mediterranean mixed forests. To achieve that, data from Spanish National Forest Inventory was used in this study to fit new mixed-effects basal area increment (BAI) models for 29 two-species compositions in Spain. A wide range of different competition structures (intra-specific, inter-specific, size-symmetric and size-asymmetric) and aridity conditions (in terms of the De Martonne Index) were included and tested into the BAI models. Parameter estimations were obtained for all possible species, mixtures and combinations by Maximum Likelihood (ML). Models with all the coefficients being significant (p Numéro de notice : A2022-059 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119955 Date de publication en ligne : 28/12/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119955 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99470
in Forest ecology and management > vol 506 (February-15 2022) . - n° 119955[article]An 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)
[article]
Titre : An integrated framework of global sensitivity analysis and calibration for spatially explicit agent-based models Type de document : Article/Communication Auteurs : Jeon-Young Kang, Auteur ; Alexander Michels, Auteur ; Andrew Crooks, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 100 - 128 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse de variance
[Termes IGN] épidémie
[Termes IGN] étalonnage de modèle
[Termes IGN] maladie virale
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] Miami
[Termes IGN] modèle de simulation
[Termes IGN] modèle orienté agent
[Termes IGN] WebSIGRésumé : (auteur) Calibration of agent-based models (ABMs) is a major challenge due to the complex nature of the systems being modeled, the heterogeneous nature of geographical regions, the varying effects of model inputs on the outputs, and computational intensity. Nevertheless, ABMs need to be carefully tuned to achieve the desirable goal of simulating spatiotemporal phenomena of interest, and a well-calibrated model is expected to achieve an improved understanding of the phenomena. To address some of the above challenges, this article proposes an integrated framework of global sensitivity analysis (GSA) and calibration, called GSA-CAL. Specifically, variance-based GSA is applied to identify input parameters with less influence on differences between simulated outputs and observations. By dropping these less influential input parameters in the calibration process, this research reduces the computational intensity of calibration. Since GSA requires many simulation runs, due to ABMs' stochasticity, we leverage the high-performance computing power provided by the advanced cyberinfrastructure. A spatially explicit ABM of influenza transmission is used as the case study to demonstrate the utility of the framework. Leveraging GSA, we were able to exclude less influential parameters in the model calibration process and demonstrate the importance of revising local settings for an epidemic pattern in an outbreak. Numéro de notice : A2022-176 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12837 Date de publication en ligne : 03/09/2021 En ligne : https://doi.org/10.1111/tgis.12837 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99832
in Transactions in GIS > vol 26 n° 1 (February 2022) . - pp 100 - 128[article]An open science and open data approach for the statistically robust estimation of forest disturbance areas / Saverio Francini in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)
[article]
Titre : An open science and open data approach for the statistically robust estimation of forest disturbance areas Type de document : Article/Communication Auteurs : Saverio Francini, Auteur ; Ronald E. McRoberts, Auteur ; Giovanni d' Amico, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coupe rase (sylviculture)
[Termes IGN] détection de changement
[Termes IGN] estimation statistique
[Termes IGN] Fagus sylvatica
[Termes IGN] Google Earth Engine
[Termes IGN] image Sentinel-MSI
[Termes IGN] Italie
[Termes IGN] méthode robuste
[Termes IGN] perturbation écologique
[Termes IGN] Quercus cerris
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus pubescens
[Termes IGN] Quercus sessiliflora
[Termes IGN] surveillance forestièreRésumé : (auteur) Forest disturbance monitoring is critical for understanding forest-related greenhouse gas emissions and for determining the role of forest management in mitigating climate change. Multiple algorithms for the automated mapping of forest disturbance using remotely sensed imagery have been developed and applied; however, variability in natural and anthropogenic disturbance phenomena, as well as image acquisition conditions, can result in maps that may be incomplete or that contain inaccuracies that prevent their use for directly estimating areas of disturbance. To reduce errors in reporting disturbance areas, stratified estimators can be applied to obtain statistically robust area estimates, while simultaneously circumventing the need to conduct a complete census or in situations where such a census may not be possible. We present a semi-automated procedure for implementation in Google Earth Engine, 3I3D-GEE, for regional to global mapping of forest disturbance (including clear-cut harvesting, fire, and wind damage) and sample-based estimation of related areas using data from the processing capacity of Google Earth Engine. Documentation for the application is also provided in Appendix A. Using Sentinel-2 (S2) imagery, our procedure was applied and tested for 2018 in Italy for which the approximately 11 million ha of forests (mostly Q. pubescens, Q. robur, Q. cerris, Q. petraea, and Fagus sylvatica) serve as an appropriate case study because national statistics on forest disturbance areas are not available. To decrease the overall standard errors of the area estimates, the sampling intensities in areas where greater variability in the form of greater commission and omission errors are expected can be increased. To this end, we augmented the predicted forest disturbance map with a buffer class consisting of a two-pixel buffer (20 m) on each side of the disturbance class boundary. We selected a reference sample of 19,300 points: a simple random sample of 9,300 points from the buffer and simple random samples of 5000 from each of the undisturbed and disturbed classes. The reference sample was photointerpreted using fine resolution orthophotos (30 cm) and S2 imagery. While the estimate of the disturbed area obtained by adding the areas of pixels classified as disturbed was 41,732 ha, the estimate obtained using the unbiased stratified estimator was 27% greater at 57,717716 ha. Regarding map accuracy, we found several omission errors in the buffer (53.4%) but none (0%) in the undisturbed map class. Similarly, among the 1035 commission errors, the majority (7 4 4) were in the buffer class. The methods presented herein provide a useful tool that can be used to estimate areas of forest disturbance, which many nations must report as part of their commitment to international conventions and treaties. In addition, the information generated can support forest management, enabling the forest sector to monitor stand-replacing forest harvesting over space and time. Numéro de notice : A2022-072 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102663 En ligne : https://doi.org/10.1016/j.jag.2021.102663 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99437
in International journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102663[article]Efficient variance component estimation for large-scale least-squares problems in satellite geodesy / Yufeng Nie in Journal of geodesy, vol 96 n° 2 (February 2022)
[article]
Titre : Efficient variance component estimation for large-scale least-squares problems in satellite geodesy Type de document : Article/Communication Auteurs : Yufeng Nie, Auteur ; Yunzhong Shen, Auteur ; Roland Pail, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] analyse de variance
[Termes IGN] champ de pesanteur terrestre
[Termes IGN] estimation statistique
[Termes IGN] GRACE
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle stochastiqueRésumé : (auteur) Efficient Variance Component Estimation (VCE) is significant to optimal data combination in large-scale least-squares problems as those encountered in satellite geodesy, where millions of observations are jointly processed to estimate a huge number of unknown parameters. In this paper, an efficient VCE algorithm with rigorous trace calculation is proposed based on the local–global parameters partition scheme in satellite geodesy, which is directly applicable to both the simplified yet common case where local parameters are unique to a single observation group and the generalized case where local parameters are shared by different groups of observations. Moreover, the Monte-Carlo VCE (MCVCE) algorithm, based on the stochastic trace estimation technique, is further extended in this paper to the generalized case. Two numerical simulation cases are investigated for gravity field model recovery to evaluate both the accuracy and efficiency of the proposed algorithm and the extended MCVCE algorithm in terms of trace calculation. Compared to the conventional algorithm, the relative trace calculation errors in the efficient algorithm are all negligibly below 10–7%, while in the MCVCE algorithm they can vary from 0.6 to 37% depending on the number of adopted random vector realizations and the specific applications. The efficient algorithm can achieve computational time reduction rates above 96% compared to the conventional algorithm for all gravity field model sizes considered in the paper. In the MCVCE algorithm, however, the time reduction rates can change from 61 to 99% for different implementations. Numéro de notice : A2022-186 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01599-9 Date de publication en ligne : 16/02/2022 En ligne : https://doi.org/10.1007/s00190-022-01599-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99907
in Journal of geodesy > vol 96 n° 2 (February 2022) . - n° 13[article]Evaluation of mapped-plot variance estimators across a range of partial nonresponse in a post-stratified national forest inventory / James A. Westfall in Canadian Journal of Forest Research, Vol 52 n° 2 (February 2022)PermalinkIntegrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan / Katsuto Shimizu in International journal of applied Earth observation and geoinformation, vol 106 (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)PermalinkSNN_flow: a shared nearest-neighbor-based clustering method for inhomogeneous origin-destination flows / Qiliang Liu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)PermalinkUsing vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)PermalinkApprentissage de représentations et modèles génératifs profonds dans les systèmes dynamiques / Jean-Yves Franceschi (2022)PermalinkBest integer equivariant position estimation for multi-GNSS RTK: a multivariate normal and t-distributed performance comparison / Robert Odolinski in Journal of geodesy, vol 96 n° 1 (January 2022)PermalinkA constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data / Jing Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkDART: An efficient 3D Monte Carlo vector radiative transfer model for remote sensing applications / Yingjie Wang (2022)PermalinkDetecting and visualizing observation hot-spots in massive volunteer-contributed geographic data across spatial scales using GPU-accelerated kernel density estimation / Guiming Zhang in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)PermalinkEmpirical comparison between stochastic and deterministic modifiers over the French Auvergne geoid computation test-bed / Ropesh Goyal in Survey review, vol 54 n° 382 (January 2022)PermalinkUne généralisation de la méthode de partage des poids dans le cas où la base de sondage est continue / Philippe Brion (2022)PermalinkGenerating GPS decoupled clock products for precise point positioning with ambiguity resolution / Shuai Liu in Journal of geodesy, vol 96 n° 1 (January 2022)PermalinkGlobal canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles / Nico Lang in Remote sensing of environment, vol 268 (January 2022)PermalinkPermalinkA method for precisely predicting satellite clock bias based on robust fitting of ARMA models / Guochao Zhang in GPS solutions, vol 26 n° 1 (January 2022)PermalinkRobust GNSS carrier phase-based position and attitude estimation theory and applications / Daniel Arias Medina (2022)PermalinkSimulation of the meltwater under different climate change scenarios in a poorly gauged snow and glacier-fed Chitral River catchment (Hindukush region) / Huma Hayat in Geocarto international, vol 37 n° 1 ([01/01/2022])PermalinkUnsupervised generative models for data analysis and explainable artificial intelligence / Mohanad Abukmeil (2022)PermalinkEstimating timber volume loss due to storm damage in Carinthia, Austria, using ALS/TLS and spatial regression models / Arne Nothdurft in Forest ecology and management, vol 502 (December-15 2021)Permalink