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Performance analysis of cross-frequency Doppler-assisted carrier phase tracking / Dun Wang in GPS solutions, vol 27 n° 3 (July 2023)  

Public [article]  inGPS solutions > vol 27 n° 3 (July 2023) . - n° 105 Titre : Performance analysis of cross-frequency Doppler-assisted carrier phase tracking Type de document : Article/Communication Auteurs : Dun Wang, Auteur ; Shuangna Zhang, Auteur ; Tong Liu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 105 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] bruit thermique [Termes IGN] erreur systématique interfréquence d'horloge [Termes IGN] fréquence [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle mathématique [Termes IGN] phase [Termes IGN] signal GNSS Résumé : (auteur) Using the Doppler frequency obtained from tracking a GNSS pilot signal to aid in tracking another signal modulated with higher rate navigation messages in a different frequency band can improve tacking robustness and lower the message demodulation threshold. Based on an analysis of received signal frequency coherence, a linearized mathematical model of the cross-frequency Doppler-assisted carrier phase tracking loop is built, a thermal noise jitter calculation equation for the assisted tracking loop is derived, and its dynamic stress response characteristics are examined. The loop design requirements for eliminating the influence of inter-frequency frequency bias are clarified, as are the cross-frequency assist signal selection criteria. Monte Carlo simulations and preliminary field tests validate the theoretical results using the B1C pilot signal-aided tracking B2b signal of the MEO satellite in the BeiDou satellite navigation system (BDS). Experimental results show that the carrier phase tracking threshold of the B2b signal can be reduced by about 4 dB. Numéro de notice : A2023-214 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-023-01434-4 En ligne : https://doi.org/10.1007/s10291-023-01434-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103143 [article]

An agent-based modeling approach for public charging demand estimation and charging station location optimization at urban scale / Zhiyan Yi in Computers, Environment and Urban Systems, vol 101 (April 2023)  

Public [article]  inComputers, Environment and Urban Systems > vol 101 (April 2023) . - n° 101949 Titre : An agent-based modeling approach for public charging demand estimation and charging station location optimization at urban scale Type de document : Article/Communication Auteurs : Zhiyan Yi, Auteur ; Bingkun Chen, Auteur ; Xiaoyue Cathy Liu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101949 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] chaîne de Markov [Termes IGN] distribution spatiale [Termes IGN] équipement collectif [Termes IGN] modèle orienté agent [Termes IGN] optimisation spatiale [Termes IGN] planification urbaine [Termes IGN] véhicule électrique [Termes IGN] zone urbaine Résumé : (auteur) As the market penetration of electric vehicles (EVs) increases, the surge of charging demand could potentially overload the power grid and disrupt infrastructure planning. Hence, an efficient deployment strategy of electrical vehicle supply equipment (EVSE) is much needed. This study attempts to address the EVSE problem from a microscopic perspective by formulating the problem in two steps: public charging demand simulation and charging station location optimization. Specifically, we apply agent-based modeling approach to produce high-resolution daily driving profiles within an urban-scale context using MATSim. Subsequently, we perform EV assignment based on socioeconomic attributes to determine EV adopters. Energy consumption model and public charging rule are specified for generating synthetic public charging demand and such demand is validated against real-world public charging records to guarantee the robustness of simulation results. In the second step, we apply a location approach – capacitated maximal coverage location problem (CMCLP) model – to reallocate existing charging stations with the objective of maximizing the coverage of total charging demands generated from the previous step under the budget and load capacity constraints. The entire framework is capable of modeling the spatiotemporal distribution of public charging demand in a bottom-up fashion, and provide practical support for future public EVSE installation. Numéro de notice : A2023-186 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2023.101949 Date de publication en ligne : 15/02/2023 En ligne : https://doi.org/10.1016/j.compenvurbsys.2023.101949 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102960 [article]

A network-constrained clustering method for bivariate origin-destination movement data / Wenkai Liu in International journal of geographical information science IJGIS, vol 37 n° 4 (April 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 4 (April 2023) . - pp 767 - 787 Titre : A network-constrained clustering method for bivariate origin-destination movement data Type de document : Article/Communication Auteurs : Wenkai Liu, Auteur ; Qiliang Liu, Auteur ; Jie Yang, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 767 - 787 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse bivariée [Termes IGN] analyse de groupement [Termes IGN] Chine [Termes IGN] hétérogénéité spatiale [Termes IGN] méthode de Monte-Carlo [Termes IGN] origine - destination [Termes IGN] réseau routier Résumé : (auteur) For bivariate origin-destination (OD) movement data composed of two types of individual OD movements, a bivariate cluster can be defined as a group of two types of OD movements, at least one of which has a high density. The identification of such bivariate clusters can provide new insights into the spatial interactions between different movement patterns. Because of spatial heterogeneity, the effective detection of inhomogeneous and irregularly shaped bivariate clusters from bivariate OD movement data remains a challenge. To fill this gap, we propose a network-constrained method for clustering two types of individual OD movements on road networks. To adaptively estimate the densities of inhomogeneous OD movements, we first define a new network-constrained density based on the concept of the shared nearest neighbor. A fast Monte Carlo simulation method is then developed to statistically estimate the density threshold for each type of OD movements. Finally, bivariate clusters are constructed using the density-connectivity mechanism. Experiments on simulated datasets demonstrate that the proposed method outperformed three state-of-the-art methods in identifying inhomogeneous and irregularly shaped bivariate clusters. The proposed method was applied to taxi and ride-hailing service datasets in Xiamen. The identified bivariate clusters successfully reveal competition patterns between taxi and ride-hailing services. Numéro de notice : A2023-206 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2022.2137879 Date de publication en ligne : 25/10/2022 En ligne : https://doi.org/10.1080/13658816.2022.2137879 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103108 [article]

Nonparametric upscaling of bark beetle infestations and management from plot to landscape level by combining individual-based with Markov chain models / Bruno Walter Pietzsch in European Journal of Forest Research, vol 142 n° 1 (February 2023)  

Public [article]  inEuropean Journal of Forest Research > vol 142 n° 1 (February 2023) . - pp 129 - 144 Titre : Nonparametric upscaling of bark beetle infestations and management from plot to landscape level by combining individual-based with Markov chain models Type de document : Article/Communication Auteurs : Bruno Walter Pietzsch, Auteur ; Chris Wudel, Auteur ; Uta Berger, Auteur Année de publication : 2023 Article en page(s) : pp 129 - 144 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne [Termes IGN] chaîne de Markov [Termes IGN] dépérissement [Termes IGN] insecte nuisible [Termes IGN] métamodèle [Termes IGN] modèle de simulation [Termes IGN] Picea abies [Termes IGN] santé des forêts [Termes IGN] Scolytinae [Termes IGN] Suisse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Linked to climate change, drivers such as increased temperatures and decreased water availability affect forest health in complex ways by simultaneously weakening tree vitality and promoting insect pest activity. One major beneficiary of climate-induced changes is the European spruce bark beetle (Ips typographus). To improve the mechanistic understanding of climate change impacts on long-term beetle infestation risks, individual-based simulation models (IBM) such as the bark beetle dispersion model IPS-SPREADS have been proven as effective tools. However, the computational costs of IBMs limit their spatial scale of application. While these tools are best suitable to simulate bark beetle dynamics on the plot level, upscaling the process to larger areas is challenging. The larger spatial scale is, nevertheless, often required to support the selection of adequate management intervention. Here, we introduce a novel two-step approach to address this challenge: (1) we use the IPS-SPREADS model to simulate the bark beetle dispersal at a local scale by dividing the research area into 250 × 250 m grid cells; and (2) we then apply a metamodel framework to upscale the results to the landscape level. The metamodel is based on Markov chains derived from the infestation probabilities of IPS-SPREADS results and extended by considering neighbor interaction and spruce dieback of each focal cell. We validated the metamodel by comparing its predictions with infestations observed in 2017 and 2018 in the Saxon Switzerland national park, Germany, and tested sanitation felling as a measure to prevent potential further outbreaks in the region. Validation showed an improvement in predictions by introducing the model extension of beetle spreading from one cell to another. The metamodel forecasts indicated an increase in the risk of infestation for adjacent forest areas. In case of a beetle mass outbreak, sanitation felling intensities of 80 percent and above seem to mitigate further outbreak progression. Numéro de notice : A2023-139 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-022-01512-1 Date de publication en ligne : 29/10/2022 En ligne : https://doi.org/10.1007/s10342-022-01512-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102694 [article]

Analysis of cycling network evolution in OpenStreetMap through a data quality prism / Raphaël Bres (2023)  

Public Titre : Analysis of cycling network evolution in OpenStreetMap through a data quality prism Type de document : Article/Communication Auteurs : Raphaël Bres, Auteur ; Veronika Peralta, Auteur ; Arnaud Le Guilcher , Auteur ; Thomas Devogele , Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Cyril de Runz, Auteur Editeur : Göttingen : Copernicus publications Année de publication : 2023 Collection : AGILE GIScience Series num. 4 Conférence : AGILE 2023, 26th international AGILE Conference on Geographic Information Science, Spatial data for design 13/06/2023 16/06/2023 Delft Pays-Bas OA Proceedings Importance : n° 3 ; 9 p. Note générale : bibliographie voir aussi le rapport de reproductibilité : https://doi.org/10.17605/OSF.IO/9KP7U Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] bicyclette [Termes IGN] méthode de Monte-Carlo [Termes IGN] mobilité territoriale [Termes IGN] mobilité urbaine [Termes IGN] modèle de simulation [Termes IGN] OpenStreetMap [Termes IGN] qualité des données [Termes IGN] voie cyclable Résumé : (auteur) Cycling practice has been constantly increasing for several years and the COVID crisis has just accelerated the process. Indeed, more and more municipalities have developed new cycle paths to facilitate cycling. Considering this increasing interest for cycling, it makes sense to study how this recent evolution is reflected in the underlying representation of the cycling network in the geographic databases. Main studies analysing the evolution of the road network focus on the motor vehicle network in the major cities of the world. These studies do not seem applicable to cycling network specially to some low population density areas or even to smaller cities. This paper analyses the changes in the cycling network through OSM data from a data freshness perspective. These changes can be either updates from changes in the real-world network or upgrades to the network. To these end, we propose a method using a Monte Carlo simulation (MCS) to analyse the frequency of changes in cycling routes in several areas with different population density, all in the Loire Valley region in France. We also define the cycling network, which is a very complex concept and we explain how it is represented in OSM data and suffers from different data quality issues. Results show that the number of changes across time are similar in areas having a similar population density, while being lower in low population density areas. These phenomena is higher in the cycling network compared to other networks. Numéro de notice : C2023-011 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : Vers HAL Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/agile-giss-4-3-2023 Date de publication en ligne : 06/06/2023 En ligne : https://doi.org/10.5194/agile-giss-4-3-2023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103308

Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography / Ihor Kozak in Urban Forestry & Urban Greening, vol 79 (January 2023)  

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Urban infrastructure expansion and artificial light pollution degrade coastal ecosystems, increasing natural-to-urban structural connectivity / Moisés A. Aguilera in Landscape and Urban Planning, vol 229 (January 2023)  

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A data-driven framework to manage uncertainty due to limited transferability in urban growth models / Jingyan Yu in Computers, Environment and Urban Systems, vol 98 (December 2022)  

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Multi-frequency simulation of ionospheric scintillation using a phase-screen model / Fernando D. Nunes in Navigation : journal of the Institute of navigation, vol 69 n° 4 (Fall 2022)  

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Modelling the future vulnerability of urban green space for priority-based management and green prosperity strategy planning in Kolkata, India: a PSR-based analysis using AHP-FCE and ANN-Markov model / Santanu Dinda in Geocarto international, vol 37 n° 22 ([10/10/2022])  

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An estimation method to reduce complete and partial nonresponse bias in forest inventory / James A. Westfall in European Journal of Forest Research, vol 141 n° 5 (October 2022)  

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Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices / Najmeh Mozaffaree Pour in Environmental Monitoring and Assessment, vol 194 n° 9 (September 2022)  

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Generating impact maps from bomb craters automatically detected in aerial wartime images using marked point processes / Christian Kruse in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)  

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DART-Lux: An unbiased and rapid Monte Carlo radiative transfer method for simulating remote sensing images / Yingjie Wang in Remote sensing of environment, vol 274 (June 2022)  

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Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference / Xiao Huang in Transactions in GIS, vol 26 n° 4 (June 2022)  

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