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scientifique

Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment / Ömer Ekmekcioğlu in Sustainable Cities and Society, vol 87 (December 2022)  

Public [article]  inSustainable Cities and Society > vol 87 (December 2022) . - n° 104195 Titre : Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment Type de document : Article/Communication Auteurs : Ömer Ekmekcioğlu, Auteur ; Kerim Koc, Auteur ; Ismail Dabanli, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104195 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse multicritère [Termes IGN] changement climatique [Termes IGN] eau [Termes IGN] milieu urbain [Termes IGN] planification urbaine [Termes IGN] pondération [Termes IGN] processus de hiérarchisation analytique floue [Termes IGN] résilience écologique [Termes IGN] ressources en eau [Termes IGN] utilisation du sol [Termes IGN] ville durable Résumé : (auteur) This study was undertaken to be a remedy to urban water scarcity phenomena having escalated consequences with the contemporaneous effects of climate change and over-urbanization. Hence, a broad list of mitigation strategies comprising 44 action plans under seven dimensions was assessed depending upon five constraints (i.e., cost-effectiveness, time/effort required, feasibility, primary benefit, and secondary benefits). To realize the overarching aim of this research, the analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) each subjected to the fuzzy set theory were employed. In this regard, the fuzzy AHP was utilized for determining the weights of constraining criteria, while the prioritization of the strategies was performed via the fuzzy TOPSIS. The results revealed that the primary benefit is the most prevailing criterion compared to its counterparts. In addition, procuring organized land use planning and limiting new growth in urban areas was found as the most promising strategy to combat urban water scarcity phenomena. The findings further highlighted the effectiveness of conducting integrated water resource planning against climate change and fostering the use of sustainable materials domestically in not only mitigating urban water scarcity but also increasing the resiliency and sustainability of the urbanized cities. Numéro de notice : A2022-818 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104195 Date de publication en ligne : 21/09/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101985 [article]

Automatic vectorization of fluvial corridor features on historical maps to assess riverscape changes / Samuel Dunesme in Cartography and Geographic Information Science, vol 49 n° 6 (November 2022)  

Public [article]  inCartography and Geographic Information Science > vol 49 n° 6 (November 2022) . - pp 512 - 527 Titre : Automatic vectorization of fluvial corridor features on historical maps to assess riverscape changes Type de document : Article/Communication Auteurs : Samuel Dunesme , Auteur ; Hervé Piegay, Auteur ; Sébastien Mustière , Auteur Année de publication : 2022 Projets : EUR H20'Lyon / Article en page(s) : pp 512 - 527 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] automatisation [Termes IGN] carte ancienne [Termes IGN] couleur (rédaction cartographique) [Termes IGN] cours d'eau [Termes IGN] détection de changement [Termes IGN] Institut national de l'information géographique et forestière (France) [Termes IGN] réseau fluvial [Termes IGN] réseau hydrographique [Termes IGN] vectorisation Résumé : (auteur) The vectorization of historical maps is an important scientific issue for understanding the dynamics of change recorded by territories. Historical maps are potentially an excellent source of data for characterizing river changes at large scales. The use of vectorized data is essential for such characterization, as well as for highlighting changes in the planform alignment of such reaches over time. At a regional network scale of several thousand kilometers of river, such work requires the vectorization of several hundred or even thousands of maps. This work proposes an automated vectorization procedure for the hydrographic network detailed in the cartographic resources of the IGN (the French National Mapping Agency). The ultimate goal is to use these historical maps to track the planform evolution of the elementary landscape units (water, bare banks, and riparian vegetation) that constitute river corridors at the basin network scale. The Historical Maps Vectorization Toolbox was developed to automatically vectorize river corridor objects (sediment banks, water surfaces, and vegetation polygons) with a high level of accuracy. The toolbox works with a 2-step process: first it classifies the colors detected on the map, then it reconstructs the objects of the fluvial corridor. We also demonstrate a practical use of the toolbox through measuring changes in the surface area of river networks of several hundred kilometers. Numéro de notice : A2022-604 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2022.2091661 Date de publication en ligne : 26/07/2022 En ligne : https://doi.org/10.1080/15230406.2022.2091661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102073 [article]

Lessons learned from using historical maps to create a digital gazetteer of historical places / Mark Polczynski in International journal of cartography, vol 8 n° 3 (November 2022)  

Public [article]  inInternational journal of cartography > vol 8 n° 3 (November 2022) . - pp 326 - 342 Titre : Lessons learned from using historical maps to create a digital gazetteer of historical places Type de document : Article/Communication Auteurs : Mark Polczynski, Auteur ; Michael Polczynski, Auteur Année de publication : 2022 Article en page(s) : pp 326 - 342 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] carte ancienne [Termes IGN] données anciennes [Termes IGN] géodatabase [Termes IGN] géoréférencement [Termes IGN] répertoire toponymique [Termes IGN] site historique [Termes IGN] système d'information historique Résumé : (auteur) The purpose of this document is to provide guidance to new and inexperienced gazetteer builders, especially those constructing a digital gazetteer of historical places using historical maps, and in particular those building a gazetteer as a means to an end of answering specific research questions vs. those building a gazetteer as an end in itself to be used by the general research community. In support of this target audience, the following is an accumulation of lessons learned while using historical maps to create digital gazetteers of historical places. The lessons cover gazetteer planning, design, and construction issues. As an overview of how to use historical maps to create a digital gazetteer of historical places, this document can provide new and inexperienced gazetteer builders with starting points for in-depth study of these and associated issues. An example gazetteer is provided to illustrate the lessons covered here. Numéro de notice : A2022-747 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2021.2007444 Date de publication en ligne : 14/12/2021 En ligne : https://doi.org/10.1080/23729333.2021.2007444 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101732 [article]

Application of a graph convolutional network with visual and semantic features to classify urban scenes / Yongyang Xu in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 10 (October 2022) . - pp 2009-2034 Titre : Application of a graph convolutional network with visual and semantic features to classify urban scenes Type de document : Article/Communication Auteurs : Yongyang Xu, Auteur ; Shuai Jin, Auteur ; Zhanlong Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2009-2034 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] extraction de traits caractéristiques [Termes IGN] matrice de co-occurrence [Termes IGN] OpenStreetMap [Termes IGN] Pékin (Chine) [Termes IGN] point d'intérêt [Termes IGN] relation spatiale [Termes IGN] réseau neuronal de graphes [Termes IGN] réseau routier [Termes IGN] scène urbaine Résumé : (auteur) Urban scenes consist of visual and semantic features and exhibit spatial relationships among land-use types (e.g. industrial areas are far away from the residential zones). This study applied a graph convolutional network with neighborhood information (henceforth, named the neighbour supporting graph convolutional neural network), to learn spatial relationships for urban scene classification. Furthermore, a co-occurrence analysis with visual and semantic features proceeded to improve the accuracy of urban scene classification. We tested the proposed method with the fifth ring road of Beijing with an overall classification accuracy of 0.827 and a Kappa coefficient of 0.769. In comparison with other methods, such as support vector machine, random forest, and general graph convolutional network, the case study showed that the proposed method improved about 10% in urban scene classification. Numéro de notice : A2022-740 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2048834 Date de publication en ligne : 10/03/2022 En ligne : https://doi.org/10.1080/13658816.2022.2048834 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101717 [article]

Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data / Michael J. Campbell in Computers, Environment and Urban Systems, vol 97 (October 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 97 (October 2022) . - n° 101866 Titre : Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data Type de document : Article/Communication Auteurs : Michael J. Campbell, Auteur ; Philip E. Dennison, Auteur ; Matthew Thompson, Auteur Année de publication : 2022 Article en page(s) : n° 101866 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données localisées [Termes IGN] Californie (Etats-Unis) [Termes IGN] chemin le moins coûteux, algorithme du [Termes IGN] données issues des réseaux sociaux [Termes IGN] durée de trajet [Termes IGN] mobilité urbaine [Termes IGN] navigation pédestre [Termes IGN] pente [Termes IGN] planification urbaine [Termes IGN] trace GPS [Termes IGN] Utah (Etas-Unis) Résumé : (auteur) Accurately predicting pedestrian travel times is critically valuable in emergency response, wildland firefighting, disaster management, law enforcement, and urban planning. However, the relationship between pedestrian movement and landscape conditions is highly variable between individuals, making it difficult to estimate how long it will take broad populations to get from one location to another on foot. Although functions exist for predicting travel rates, they typically oversimplify the inherent variability of pedestrian travel by assuming the effects of landscapes on movement are universal. In this study, we present an approach for predicting the variability in pedestrian travel rates and times using a large, crowdsourced database of GPS tracks. Acquired from the outdoor recreation website AllTrails, these tracks represent nearly 2000 hikes on a diverse range of trails in Utah and California, USA. We model travel rates as a function of the slope of the terrain by generating a series of non-linear percentile models from the 2.5 th to the 97.5 th by 2.5 percentiles. The 50 th percentile model, representing the hiking speed of the typical individual, demonstrates marked improvement over existing slope-travel rate functions when compared to an independent test dataset. Our results demonstrate novel capacity to estimate travel time variability, with modeled percentiles being able to predict actual percentiles with less than 10% error. Travel rate functions can also be applied to least cost path analysis to provide variability in travel times. Numéro de notice : A2022-599 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2022.101866 Date de publication en ligne : 20/08/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101866 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101452 [article]

Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions / Di Zhu in Geoinformatica [en ligne], vol 26 n° 4 (October 2022)  

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Prediction of suspended sediment concentration using hybrid SVM-WOA approaches / Sandeep Samantaray in Geocarto international, vol 37 n° 19 ([15/09/2022])  

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An exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data / Jue Wang in Cartography and Geographic Information Science, Vol 49 n° 5 (September 2022)  

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Deep learning method for Chinese multisource point of interest matching / Pengpeng Li in Computers, Environment and Urban Systems, vol 96 (September 2022)  

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Exploring multi-modal evacuation strategies for a landlocked population using large-scale agent-based simulations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)  

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Experiencing virtual geographic environment in urban 3D participatory e-planning: A user perspective / Thibaud Chassin in Landscape and Urban Planning, vol 224 (August 2022)  

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Parcel Manager: A parcel reshaping model incorporating design rules of residential development / Maxime Colomb in Transactions in GIS, vol 26 n° 6 (September 2022)  

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3D-GIS parametric modelling for virtual urban simulation using CityEngine / Ibrahim M. Badwi in Annals of GIS, vol 28 n° 3 (July 2022)  

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Geographic knowledge graph attribute normalization: Improving the accuracy by fusing optimal granularity clustering and co-occurrence analysis / Chuan Yin in ISPRS International journal of geo-information, vol 11 n° 7 (July 2022)  

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3D modeling method for dome structure using digital geological map and DEM / Xian-Yu Liu in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)  

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