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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)  

Public [article]  inSustainable Cities and Society > vol 89 (February 2023) . - n° 104337 Titre : Analysing urban growth using machine learning and open data: An artificial neural network modelled case study of five Greek cities Type de document : Article/Communication Auteurs : Pavlos Tsagkis, Auteur ; Efthimios Bakogiannis, Auteur ; Alexandros Nikitas, Auteur Année de publication : 2023 Article en page(s) : n° 104337 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] Corine (base de données) [Termes IGN] croissance urbaine [Termes IGN] données localisées libres [Termes IGN] étalement urbain [Termes IGN] Grèce [Termes IGN] modèle de simulation [Termes IGN] modèle numérique de surface [Termes IGN] modèle orienté agent [Termes IGN] OpenStreetMap [Termes IGN] planification urbaine [Termes IGN] réseau neuronal artificiel Résumé : (auteur) Urban development if not planned and managed adequately can be unsustainable. Urban growth models have been a powerful toolkit to help tackling this challenge. In this paper, we use a machine learning approach, to apply an urban growth model to five of the largest cities in Greece. Specifically, we first develop a methodology to collect, organise, handle and transform historical open spatial data, concerning various impact factors, into machine learning data. Such factors involve social, economic, biophysical, neighbouring-related and political driving forces, which must be transformed into tabular data. We also provide an artificial neural network (ANN) model and the methodology to train and evaluate it using goodness-of-fit metrics, which in turn provide the best weights of impact factors. Finally, we execute a prediction for 2030, presenting the results and output maps for each of the five case study cities. As our study is based on pan-European datasets, our model can be used for any area within Europe, using the open-source utility developed to support it. In this sense, our work provides local policy-makers and urban planners with an instrument that could help them analyse various future development scenarios and take the right decisions going forward. Numéro de notice : A2023-116 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.104337 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104337 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102486 [article]

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

Public [article]  inLandscape and Urban Planning > vol 230 (February 2023) . - n° 104624 Titre : Long-term changes in 3D urban form in four Spanish cities Type de document : Article/Communication Auteurs : Dario Domingo, Auteur ; Jasper van Vliet, Auteur ; Anna M. Hersperger, Auteur Année de publication : 2023 Article en page(s) : n° 104624 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] croissance urbaine [Termes IGN] densification [Termes IGN] données cadastrales [Termes IGN] données lidar [Termes IGN] Espagne [Termes IGN] étalement urbain [Termes IGN] hauteur du bâti [Termes IGN] morphologie urbaine [Termes IGN] périphérie urbaine Résumé : (auteur) Three-dimensional urban form has a considerable influence on urban sustainability, being the reason spatial planning regulate it. Yet, we know very little about the development of building density and building height over time. In this study, we characterize the horizontal and vertical patterns of urban development in Barcelona, Madrid, Valencia, and Zaragoza between 1965 and 2015. Our analysis is based on a unique combination of cadastral data and LiDAR point clouds, which we use to characterize building footprint, height, and volume, at decadal intervals. Subsequently, we characterize urban expansion and densification processes using building volume and Urban Form Types. We find that height of new buildings shows a significant downward trend during the 70′s for the four urban areas and a decreasing trend after the 2008 real estate bubble for the cases of Barcelona and Valencia. Over the analyzed period a decrease of 116, 313, 217 and 157 cm in average building height was observed for Barcelona, Madrid, Valencia, and Zaragoza, respectively. Urbanized volume of all cities together has expanded by roughly 350% between 1950 and 2015. Sparse built-up form showed the largest absolute increase, although it contains only a low fraction of new built-up volume. A clear trend towards expansion is observed in city outskirts and the development of new urban clusters in municipalities closer to the main city. At the same time, settlements have followed incremental steps towards densification of the city-cores over time. This study provides a first step towards comprehensive understanding of long-term changes in 3D urban form, which can inform the development of policies that target the third dimension in urban form to steer sustainable urban growth. Numéro de notice : A2023-012 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.landurbplan.2022.104624 Date de publication en ligne : 09/11/2023 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104624 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102124 [article]

HGAT-VCA: Integrating high-order graph attention network with vector cellular automata for urban growth simulation / Xuefeng Guan in Computers, Environment and Urban Systems, vol 99 (January 2023)  

Public [article]  inComputers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101900 Titre : HGAT-VCA: Integrating high-order graph attention network with vector cellular automata for urban growth simulation Type de document : Article/Communication Auteurs : Xuefeng Guan, Auteur ; Weiran Xing, Auteur ; Jingbo Li, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101900 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] adjacence [Termes IGN] attention (apprentissage automatique) [Termes IGN] automate cellulaire [Termes IGN] changement d'utilisation du sol [Termes IGN] croissance urbaine [Termes IGN] étalement urbain [Termes IGN] hétérogénéité spatiale [Termes IGN] modèle de simulation [Termes IGN] Queensland (Australie) [Termes IGN] réseau neuronal de graphes [Termes IGN] voisinage (relation topologique) [Termes IGN] zone tampon Résumé : (auteur) Since urban growth results from frequent spatial interaction between urban units, adequate representation of spatial interaction is important for urban growth modeling. Among urban growth models, vector-based cellular automata (VCA) excels at expressing spatial interaction with realistic entities, and has accordingly been used extensively in recent studies. However, two issues with VCA modeling still remain: 1) inefficient manual selection of interaction targets with various neighborhood configurations; 2) inaccurate quantification of interaction intensity due to ignorance of spatial heterogeneity in entity interaction. To address these two limitations, this study proposed a novel VCA model with high-order graph attention network (HGAT-VCA). In this model, a graph structure is first built from the topology adjacency relationship between cadastral parcels. In terms of the HGAT components, the original 1st-order parcel neighborhood is extended to high-order to capture the distant dependency, while graph attention is applied to quantify the heterogeneous interaction intensity between parcels. Finally, the conversion probability obtained by HGAT is integrated with VCA to simulate urban land use change. Land use data from the Moreton Bay Region in Queensland, Australia from 2005 to 2009 are selected to verify the proposed HGAT-VCA model. Experimental results illustrate that HGAT-VCA outperforms four classical CA models and achieves the highest simulation accuracy (e.g., the increase of FoM is about 40.7%). In addition, extensive neighborhood configuration experiments show that with HGAT only tuning discrete topological order can generate similar accuracy results compared with the repetitive buffer-based neighborhood configuration, and this can significantly improve the calibration efficiency of VCA models. Numéro de notice : A2023-031 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101900 Date de publication en ligne : 19/10/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101900 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102163 [article]

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)  

Public [article]  inLandscape and Urban Planning > vol 229 (January 2023) . - n° 104609 Titre : Urban infrastructure expansion and artificial light pollution degrade coastal ecosystems, increasing natural-to-urban structural connectivity Type de document : Article/Communication Auteurs : Moisés A. Aguilera, Auteur ; Maria Gracia González, Auteur Année de publication : 2023 Article en page(s) : n° 104609 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] ArcGIS [Termes IGN] Chili [Termes IGN] croissance urbaine [Termes IGN] dégradation de l'environnement [Termes IGN] écosystème [Termes IGN] étalement urbain [Termes IGN] habitat (nature) [Termes IGN] intensité lumineuse [Termes IGN] littoral [Termes IGN] méthode de Monte-Carlo [Termes IGN] paysage urbain [Termes IGN] pollution lumineuse [Termes IGN] urbanisme Résumé : (auteur) Urbanization is provoking habitat loss and fragmentation, driving rapid landscape transformation worldwide. Remnant habitats in urban areas can be especially prone to degradation by human activities at short time scales, and poor planning during urban expansion can erode their structural and functional connectivity. Foredunes in particular are threatened significantly by human activities, including coastal urban infrastructure expansion, by bulldozing them and/or by interrupting their continuity across the shoreline, and also by associated light pollution. However, there is still scarce quantification about how urban processes determine changes in remnant habitat extent and modify the configuration of structural connectivity in coastal urban settings. Using an expanding conurbation located in north-central Chile (∼29°S) as model system, we investigated the rate of coastal foredune loss and spatial fragmentation due to urban expansion, and the change in the type of structural connectivity, i.e. with other natural habitats vs with urban infrastructure. Based on map analyses of structural connectivity among habitats and with urban infrastructure through time, we estimated foredune habitat extent and fragmentation and their shared border with other habitats and built infrastructure during two time intervals, 2010–2015 and 2015–2020. Distribution and intensity of light pollution on present foredunes were also quantified in situ through field sampling. We found 36 % decline in foredune area and increase in their connection with urban infrastructure. Urban wetlands and parallel dunes also experienced persistent area loss and increase in connection with urban infrastructure. Light pollution was intense in the foredune-beach ecotone. Given the rapid erosion of functional and structural connectivity of natural habitats, it becomes imperious to halt the reduction of remnant habitats and ecotones, and improve natural corridors in urban settings. Numéro de notice : A2023-127 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.landurbplan.2022.104609 Date de publication en ligne : 17/10/2022 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104609 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102507 [article]

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)  

Public [article]  inComputers, Environment and Urban Systems > vol 98 (December 2022) . - n° 101892 Titre : A data-driven framework to manage uncertainty due to limited transferability in urban growth models Type de document : Article/Communication Auteurs : Jingyan Yu, Auteur ; Alex Hagen-Zanker, Auteur ; Naratip Santitissadeekorn, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101892 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] automate cellulaire [Termes IGN] changement d'utilisation du sol [Termes IGN] croissance urbaine [Termes IGN] estimation bayesienne [Termes IGN] étalement urbain [Termes IGN] Europe (géographie politique) [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] modèle stochastique [Termes IGN] simulation dynamique Résumé : (auteur) The processes of urban growth vary in space and time. There is a lack of model transferability, which means that models estimated for a particular study area and period are not necessarily applicable for other periods and areas. This problem is often addressed through scenario analysis, where scenarios reflect different plausible model realisations based typically on expert consultation. This study proposes a novel framework for data-driven scenario development which, consists of three components - (i) multi-area, multi-period calibration, (ii) growth mode clustering, and (iii) cross-application. The framework finds clusters of parameters, referred to as growth modes: within the clusters, parameters represent similar spatial development trajectories; between the clusters, parameters represent substantially different spatial development trajectories. The framework is tested with a stochastic dynamic urban growth model across European functional urban areas over multiple time periods, estimated using a Bayesian method on an open global urban settlement dataset covering the period 1975–2014. The results confirm a lack of transferability, with reduced confidence in the model over the validation period, compared to the calibration period. Over the calibration period the probability that parameters estimated specifically for an area outperforms those for other areas is 96%. However, over an independent validation period, this probability drops to 72%. Four growth modes are identified along a gradient from compact to dispersed spatial developments. For most training areas, spatial development in the later period is better characterized by one of the four modes than their own historical parameters. The results provide strong support for using identified parameter clusters as a tool for data-driven and quantitative scenario development, to reflect part of the uncertainty of future spatial development trajectories. Numéro de notice : A2022-799 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101892 Date de publication en ligne : 08/10/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101966 [article]

Integration of geospatial technologies with multiple regression model for urban land use land cover change analysis and its impact on land surface temperature in Jimma City, southwestern Ethiopia / Mitiku Badasa Moisa in Applied geomatics, vol 14 n° 4 (December 2022)  

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A whale optimization algorithm–based cellular automata model for urban expansion simulation / Yuan Ding in International journal of applied Earth observation and geoinformation, vol 115 (December 2022)  

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Driving factors of urban sprawl in the Romanian plain. Regional and temporal modelling using logistic regression / Ines Grigorescu in Geocarto international, vol 37 n° 24 ([20/10/2022])  

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Simulation of the potential impact of urban expansion on regional ecological corridors: A case study of Taiyuan, China / Wei Hou in Sustainable Cities and Society, vol 83 (August 2022)  

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Dynamic linkage between urbanization, electrical power consumption, and suitability analysis using remote sensing and GIS techniques / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)  

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Urban geomorphology of a historical city straddling the Tanaro River (Alessandria, NW Italy) / Andrea Mandarino in Journal of maps, vol 17 n° 4 (October 2021)  

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Urban 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])  

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Spatiotemporal patterns of urbanization during the last four decades in Switzerland and their impacts on urban heat islands / Marti Bosch Padros (2021)  

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Détection du changement de l'étalement urbain au bas-Sahara algérien : apport de la télédétection spatiale et des SIG, cas de la ville de Biskra (Algérie) / Assoule Dechaicha in Revue Française de Photogrammétrie et de Télédétection, n° 222 (novembre 2020)  

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Urban expansion in Auckland, New Zealand: a GIS simulation via an intelligent self-adapting multiscale agent-based model / Tingting Xu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)  

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