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Detecting spatiotemporal propagation patterns of traffic congestion from fine-grained vehicle trajectory data / Haoyi Xiong in International journal of geographical information science IJGIS, vol 37 n° 5 (May 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 5 (May 2023) . - pp 1157-1179 Titre : Detecting spatiotemporal propagation patterns of traffic congestion from fine-grained vehicle trajectory data Type de document : Article/Communication Auteurs : Haoyi Xiong, Auteur ; Xun Zhou, Auteur ; David A. Bennett, Auteur Année de publication : 2023 Article en page(s) : pp 1157-1179 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] déformation temporelle dynamique (algorithme) [Termes IGN] détection d'anomalie [Termes IGN] données spatiotemporelles [Termes IGN] événement [Termes IGN] flux [Termes IGN] gestion de trafic [Termes IGN] réseau routier [Termes IGN] trafic routier Résumé : (auteur) Traffic congestion on a road segment typically begins as a small-scale spatiotemporal event that can then propagate throughout a road network and produce large-scale disruptions to a transportation system. In current techniques for the analysis of network flow, data is often aggregated to relatively large (e.g. 5 min) discrete time steps that obscure the small-scale spatiotemporal interactions that drive larger-scale dynamics. We propose a new method that handles fine-grained data to better capture those dynamics. Propagation patterns of traffic congestion are represented as spatiotemporally connected events. Each event is captured as a time series at the temporal resolution of the available trajectory data and at the spatial resolution of the network edge. The spatiotemporal propagation patterns of traffic congestion are captured using Dynamic Time Warping and represented as a set of directed acyclic graphs of spatiotemporal events. Results from this method are compared to an existing method using fine-grained data derived from an agent-based model of traffic simulation. Our method outperforms the existing method. Our method also successfully detects congestion propagation patterns that were reported by media news using sparse real-world data derived from taxis. Numéro de notice : A2023-225 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2023.2178653 Date de publication en ligne : 22/02/2023 En ligne : https://doi.org/10.1080/13658816.2023.2178653 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103177 [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]

An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong / Hai-Min Lyu in Sustainable Cities and Society, vol 91 (April 2023)  

Public [article]  inSustainable Cities and Society > vol 91 (April 2023) . - n° 104427 Titre : An improved MCDM combined with GIS for risk assessment of multi-hazards in Hong Kong Type de document : Article/Communication Auteurs : Hai-Min Lyu, Auteur ; Zhen-Yu Yin, Auteur Année de publication : 2023 Article en page(s) : n° 104427 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse multicritère [Termes IGN] Hong-Kong [Termes IGN] processus de hiérarchisation analytique floue [Termes IGN] risque naturel [Termes IGN] système d'information géographique [Termes IGN] zone à risque Résumé : (auteur) Hong Kong frequently suffers from multi-hazards such as floods, muddy-water flows and landslides induced by rainstorms. This study presents an improved multi criteria decision making (MCDM) approach with integrating the interval numbers into fuzzy analytical hierarchy process (FAHP) to assess multi-hazard risks. To illustrate the efficiency of the improved MCDM method, the AHP, interval-FAHP and analytical network process (ANP) were incorporated into a geographical information system (GIS, abbreviated as AHP-GIS, interval-FAHP-GIS, and ANP-GIS) to assess the risks of multi-hazards (e.g., floods, muddy-water flows, and landslides) in Hong Kong. The assessed multi-risks indicated that the percentages of areas with a high risk of flood, muddy-water flow, and landslide were more than 15%, 17%, and 18%, respectively. The results demonstrated that MCDM methods considered multi-criteria contributions on multi hazards. Different assessment factors contributed different importance on different multi-hazard risks. The comparison indicates that interval-FAHP-GIS perform better than AHP-GIS and ANP-GIS in capturing high-risk areas. The interval-FAHP-GIS method adopts interval fuzzy numbers instead of crisp numbers in AHP-GIS to reflect the degree of importance of assessment factors, which increases the accuracy of the assessed multi-risks. Numéro de notice : A2023-150 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2023.104427 Date de publication en ligne : 27/01/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104427 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102823 [article]

Evaluating future railway-induced urban growth of twelve cities using multiple SLEUTH models with open-source geospatial inputs / Alvin Christopher G. Varquez in Sustainable Cities and Society, vol 91 (April 2023)  

Public [article]  inSustainable Cities and Society > vol 91 (April 2023) . - n° 104442 Titre : Evaluating future railway-induced urban growth of twelve cities using multiple SLEUTH models with open-source geospatial inputs Type de document : Article/Communication Auteurs : Alvin Christopher G. Varquez, Auteur ; Sifan Dong, Auteur ; Shinya Hanaoka, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104442 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] changement d'utilisation du sol [Termes IGN] croissance urbaine [Termes IGN] gare [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] réseau ferroviaire [Termes IGN] système d'information géographique [Termes IGN] urbanisation Résumé : (auteur) Plausible urban growth projections aid in the understanding and treatment of multidisciplinary issues faced in society. In this work, we investigated the possible effects of train stations on urban growth by comparing urban projections from a cellular-automata-based land use change model, named SLEUTH, with versions (i.e. SLEUTsH and SLEUTsHGA introduced in this study) that can consider railway-induced urban growth and those (i.e. SLEUTH and SLEUTHGA) that do not. It was found that the influence of the railway stations on urban growth varied with time and according to each city. In general, railway stations induced urbanization in their immediate surroundings. However, edge growth, which is growth at the urban boundaries was slow in the first five years of the future prediction. As demonstrated by the higher urban growth rates simulated for the first few years in the SLEUTsH cases than the SLEUTH cases, the presence of railway stations will lead to more rapid urbanization in the 2040s. Mainly relying on publicly available GIS datasets, this work demonstrates the potential for modeling railway-induced urban growth on a global scale. The findings can be further confirmed with other cellular-automata models using a similar methodology. Numéro de notice : A2023-151 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.scs.2023.104442 Date de publication en ligne : 08/02/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104442 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102824 [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]

Mapping population distribution from open address data: application to mainland Portugal / Nelson Mileu in Journal of maps, vol 18 n° 3 (March 2023)  

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SALT: A multifeature ensemble learning framework for mapping urban functional zones from VGI data and VHR images / Hao Wu in Computers, Environment and Urban Systems, vol 100 (March 2023)  

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A spatial distribution: Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil / Jiawei Liu in Science of the total environment, vol 859 n° 1 (February 2023)  

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Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities / Pavlos Tsagkis in Sustainable Cities and Society, vol 89 (February 2023)  

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Identification of enclaves and exclaves by computation based on point-set topology / Xiaonan Wang in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)  

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Long-term changes in 3D urban form in four Spanish cities / Dario Domingo in Landscape and Urban Planning, vol 230 (February 2023)  

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Measuring spatial nonstationary effects of POI-based mixed use on urban vibrancy using Bayesian spatially varying coefficients model / Zensheng Wang in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)  

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Multi-agent reinforcement learning to unify order-matching and vehicle-repositioning in ride-hailing services / Mingyue Xu in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)  

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Stochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data / Parvez Rana in Landscape and Urban Planning, vol 230 (February 2023)  

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

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