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Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata / Aditya Tafta Nugraha in Computers, Environment and Urban Systems, vol 92 (March 2022)
[article]
Titre : Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata Type de document : Article/Communication Auteurs : Aditya Tafta Nugraha, Auteur ; Ben J. Waterson, Auteur ; Simon P. Blainey, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] dynamique spatiale
[Termes IGN] Grande-Bretagne
[Termes IGN] interaction spatiale
[Termes IGN] modèle orienté agent
[Termes IGN] morphologie urbaine
[Termes IGN] planification urbaine
[Termes IGN] port
[Termes IGN] transport urbain
[Termes IGN] utilisation du solRésumé : (auteur) The urban morphology is characterised by self-organisation where interactions of multiple agents produce emerging patterns on the urban form. Port-urban relationship added to the complexity of port cities' urban form. Most urban cellular automata (CA) models simulate land-use evolution through transition rules representing multi-factored local interactions. However, calibration of CA-based urban land use and transport interaction (LUTI) models often utilise manual methods due to complexity of the process. This limits insights on urban interactions to a few explored settlements and prevents applications for planning and assessment of transport policies in other contexts. This paper, therefore, addresses three main points. The paper (i) demonstrates an improved method for the calibration of CA-based LUTI models, (ii) contributes to a better understanding of the urban dynamics in port city systems by quantifying generalizable interactions from a wide range of port-urban settlements, and (iii) illustrates how the use of these interactions in a simulation model can allow long-term impact predictions of planning interventions. These were done by formulating a model in a similar structure as a neural network model to enable automatic calibration using an application of the gradient-descent algorithm. The model was then used to quantify the dynamics between land-use, geographic, and transport factors in 46 port-based and 10 non-port settlements across Great Britain, thus enabling cross-sectional analysis. Cluster analysis of the calibrated interactions in the study areas was conducted to examine the variations of these interactions. This produced two main groups. In the first group, consisting larger settlements, connections between ports and other urban activities were weaker than in the second group which consisted of smaller port-settlements. Overall, the findings of the research are consistent with existing evidence in the port-cities literature but go further in quantifying the interaction between urban agents within port-urban systems of various sizes and types. These quantified interactions will enable planners to better predict the longer-term consequences of their interventions. Numéro de notice : A2022-084 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101733 Date de publication en ligne : 25/11/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99489
in Computers, Environment and Urban Systems > vol 92 (March 2022)[article]Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)
[article]
Titre : Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis Type de document : Article/Communication Auteurs : Kai Zhang, Auteur ; Zhen Qian, Auteur ; Yue Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage profond
[Termes IGN] cartographie du bruit
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] distribution spatiale
[Termes IGN] image Streetview
[Termes IGN] lutte contre le bruit
[Termes IGN] milieu urbain
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] pollution acoustique
[Termes IGN] trafic routier
[Termes IGN] ville durableRésumé : (auteur) Road noise barriers (RNBs) are important urban infrastructures to relieve the harm of traffic noise pollution for citizens. Therefore, obtaining the spatial distribution characteristics of RNBs, such as precise positions and mileage, can be of great help for obtaining more accurate urban noise maps and assessing the quality of the urban living environment for sustainable urban development. However, an effective and efficient method for identifying RNBs and acquiring their attributes in large areas is scarce. This study constructs an ensemble classification model (ECM) to automatically identify RNBs at the city level based on Baidu Street View (BSV). Firstly, the bootstrap sampling method is proposed to build a street view image-based train set, where the effect of imbalanced categories of samples was reduced by adding confusing negative samples. Secondly, two state-of-the-art deep learning models, ResNet and DenseNet, are ensembled to construct an ECM based on the bagging framework. Finally, a post-processing method has been proposed based on geospatial analysis to eliminate street view images (SVIs) that are misclassified as RNBs. This study takes Suzhou, China as the study area to validate the proposed method. The model achieved an accuracy and F1-score of 0.98 and 0.90, respectively. The total mileage of the RNBs in Suzhou was 178,919 m. The results demonstrated the performance of the proposed RNBs identification framework. The significance of obtaining RNBs attributes for accelerating sustainable urban development has been demonstrated through the case of photovoltaic noise barriers (PVNBs). Numéro de notice : A2022-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.scs.2021.103598 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1016/j.scs.2021.103598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100167
in Sustainable Cities and Society > vol 78 (March 2022) . - n° 103598[article]Simulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])
[article]
Titre : Simulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India Type de document : Article/Communication Auteurs : Vaibhav Kumar, Auteur ; Arnab Jana, Auteur ; Krithi Ramamritham, Auteur Année de publication : 2022 Article en page(s) : pp 1084 - 1099 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] apprentissage automatique
[Termes IGN] bâtiment
[Termes IGN] Bombay
[Termes IGN] incendie
[Termes IGN] modèle de régression
[Termes IGN] planification urbaine
[Termes IGN] prévention des risques
[Termes IGN] régression linéaire
[Termes IGN] zone urbaineRésumé : (auteur) The article addresses the void in developing analytical methods concerning to design urban configurations that could reduce fire risks, and, thus, could help in achieving sustainable goals. A novel algorithm is developed to generate alternative Urban Built Form (UBF) models that could be less susceptible to fire compared to the existing built-form. Fire susceptibility of a generated UBF is predicted using a developed linear regression model. The algorithm considers existing regulations to derive rules and develop scenarios that might be effective in building fire-resilient cities. The outcomes of the simulations showed a significant decrease in the fire susceptibility of the southern region of Mumbai city. Moreover, for a certain simulated scenario the predicted UBF could accommodate twice the current population while being less susceptible than the existing UBF. The proposed techniques and methods can act as a decision-making tool in taking pre-emptive planning measures to develop fire resilient cities. Numéro de notice : A2022-395 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1756463 Date de publication en ligne : 28/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1756463 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100689
in Geocarto international > vol 37 n° 4 [15/02/2022] . - pp 1084 - 1099[article]Emerging technologies for smart cities’ transportation: Geo-information, data analytics and machine learning approaches / Li-Minn Ang in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)
[article]
Titre : Emerging technologies for smart cities’ transportation: Geo-information, data analytics and machine learning approaches Type de document : Article/Communication Auteurs : Li-Minn Ang, Auteur ; Jasmine Kah Phooi Seng, Auteur ; Ericmoore Ngharamike, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] données massives
[Termes IGN] planification urbaine
[Termes IGN] système de transport intelligent
[Termes IGN] trafic routier
[Termes IGN] transport collectif
[Termes IGN] transport urbain
[Termes IGN] ville intelligente
[Termes IGN] zone urbaineRésumé : (auteur) With the recent increase in urban drift, which has led to an unprecedented surge in urban population, the smart city (SC) transportation industry faces a myriad of challenges, including the development of efficient strategies to utilize available infrastructures and minimize traffic. There is, therefore, the need to devise efficient transportation strategies to tackle the issues affecting the SC transportation industry. This paper reviews the state-of-the-art for SC transportation techniques and approaches. The paper gives a comprehensive review and discussion with a focus on emerging technologies from several information and data-driven perspectives including (1) geoinformation approaches; (2) data analytics approaches; (3) machine learning approaches; (4) integrated deep learning approaches; (5) artificial intelligence (AI) approaches. The paper contains core discussions on the impacts of geo-information on SC transportation, data-driven transportation and big data technology, machine learning approaches for SC transportation, innovative artificial intelligence (AI) approaches for SC transportation, and recent trends revealed by using integrated deep learning towards SC transportation. This survey paper aimed to give useful insights to researchers regarding the roles that data-driven approaches can be utilized for in smart cities (SCs) and transportation. An objective of this paper was to acquaint researchers with the recent trends and emerging technologies for SC transportation applications, and to give useful insights to researchers on how these technologies can be exploited for SC transportation strategies. To the best of our knowledge, this is the first comprehensive review that examines the impacts of the various five driving technological forces—geoinformation, data-driven and big data technology, machine learning, integrated deep learning, and AI—in the context of SC transportation applications. Numéro de notice : A2022-118 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11020085 Date de publication en ligne : 24/01/2022 En ligne : https://doi.org/10.3390/ijgi11020085 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99649
in ISPRS International journal of geo-information > vol 11 n° 2 (February 2022) . - n° 85[article]Raw GIS to 3D road modeling for real-time traffic simulation / Yacine Amara in The Visual Computer, vol 38 n° 1 (January 2022)
[article]
Titre : Raw GIS to 3D road modeling for real-time traffic simulation Type de document : Article/Communication Auteurs : Yacine Amara, Auteur ; Abdenour Amamra, Auteur ; Salim Khemis, Auteur Année de publication : 2022 Article en page(s) : pp 239 - 256 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] comportement
[Termes IGN] graphe topologique
[Termes IGN] intersection spatiale
[Termes IGN] modèle de simulation
[Termes IGN] modélisation 3D
[Termes IGN] navigation virtuelle
[Termes IGN] planification urbaine
[Termes IGN] système d'information géographique
[Termes IGN] système multi-agents
[Termes IGN] temps réel
[Termes IGN] trafic routier
[Termes IGN] trajectoire (véhicule non spatial)Résumé : (auteur) In this work, we propose a new approach to road modeling and 3D traffic simulation. Based on the raw geographic information system (GIS) data laid out as sparse polylines with attributes, we compute a more adequate functional description for real-time simulation of on-road vehicle animation. The proposed approach begins with a filtering/subdivision module where the raw polylines are transformed into a graph of functional road segments as arcs and the nodes as intersections. Then, the vehicle speed profile is computed based on its dynamics, its neighborhood and the curvature profile of the road. Afterward, a multi-agent system is proposed in order to handle a large number of simulated vehicle/driver couples. Finally, we deploy a 3D rendering engine to display the computed 3D simulation on screen. The resulting model satisfies most of the real road features for traffic simulation including road interchanges, roundabouts, intersections, lanes, etc. More importantly, the simulated driving qualitatively mimics the real behavior of the drivers/vehicles on the road as can be seen in the accompanying video (RTSP video). We also validate our findings with a technical assessment based on macroscopic and microscopic traffic simulation metrics in several road traffic scenarios. Numéro de notice : A2022-160 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s00371-020-02013-1 Date de publication en ligne : 01/01/2022 En ligne : https://doi.org/10.1007/s00371-020-02013-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99777
in The Visual Computer > vol 38 n° 1 (January 2022) . - pp 239 - 256[article]Recurrent origin–destination network for exploration of human periodic collective dynamics / Xiaojian Chen in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkCultivating historical heritage area vitality using urban morphology approach based on big data and machine learning / Jiayu Wu in Computers, Environment and Urban Systems, vol 91 (January 2022)PermalinkGIS-based survey over the public transport strategy: An instrument for economic and sustainable urban traffic planning / Gabriela Droj in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)PermalinkThe spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) / Muhammad Amir Siddique in Remote sensing, vol 13 n° 22 (November-2 2021)PermalinkAccess to urban parks: Comparing spatial accessibility measures using three GIS-based approaches / Siqin Wang in Computers, Environment and Urban Systems, vol 90 (November 2021)PermalinkAnalytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)PermalinkEvaluating urban intensity through a city information model - intermediate results from an action research project / Adeline Deprêtre in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol VIII-4/W2-2021 ([07/10/2021])PermalinkSpatial structure system of land use along urban rail transit based on GIS spatial clustering / Yu Gao in European journal of remote sensing, vol 54 sup 2 (2021)PermalinkUrban geomorphology of a historical city straddling the Tanaro River (Alessandria, NW Italy) / Andrea Mandarino in Journal of maps, vol 17 n° 4 (October 2021)PermalinkGIS-based logic scoring of preference method for urban densification suitability analysis / Shuoge Shen in Computers, Environment and Urban Systems, vol 89 (September 2021)PermalinkUnderstanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors / Feng Gao in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)PermalinkApplication of GIS tools in the measurement analysis of urban spatial layouts using the square grid method / Łukasz Musiaka in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkImproving urban land cover classification with combined use of Sentinel-2 and Sentinel-1 imagery / Bin Hu in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkMapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America / Bin Chen in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkA cellular-automata model for assessing the sensitivity of the street network to natural terrain / Jeeno Soa George in Annals of GIS, vol 27 n° 3 (July 2021)PermalinkPedestrian fowl prediction in open public places using graph convolutional network / Menghang Liu in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)PermalinkNumerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future / Tamás Gál in Computers, Environment and Urban Systems, vol 87 (May 2021)PermalinkLearning from the informality. Using GIS tools to analyze the structure of autopoietic urban systems in the “smart perspective” / Valerio Di pinto in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)PermalinkSpatial analysis of subway passenger traffic in Saint-Petersburg / Tatiana Baltyzhakova in Geodesy and cartography, vol 47 n° 1 (January 2021)PermalinkUrban growth analysis and simulations using cellular automata and geo-informatics: comparison between Almaty and Astana in Kazakhstan / Aigerim Ilyassova in Geocarto international, vol 36 n° 5 ([15/03/2021])Permalink