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Urban climate services: climate impact projections and their uncertainties at city scale / Bert Van Schaeybroeck in FMI's climate bulletin research letters, vol 2020 n° 1 (Spring 2020)    

Public [article]  inFMI's climate bulletin research letters > vol 2020 n° 1 (Spring 2020) . - pp 12 - 13 Titre : Urban climate services: climate impact projections and their uncertainties at city scale Type de document : Article/Communication Auteurs : Bert Van Schaeybroeck, Auteur ; Bénédicte Bucher , Auteur ; et al., Auteur Année de publication : 2020 Projets : URCLIM / Bucher, Bénédicte Article en page(s) : pp 12 - 13 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] impact sur l'environnement [Termes descripteurs IGN] incertitude géométrique [Termes descripteurs IGN] ville Résumé : (auteur) In many cities across Europe, both urban authorities and private actors have made strong commitments to adapt to future climate changes. Although a lot of climate information is available at the global and regional scale, this is often not the case at the local urban scale. Moreover, such information should account for a wide range of uncertainty factors ranging from global to city-scale development scenarios to uncertainties due to model errors. In an effort to lay the methodological groundworks for reliable urban climate services, URCLIM explores a compound handling of these uncertainties for various European cities and applies it to the assessment of adaptation measures. Numéro de notice : A2020-366 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.35614/ISSN-2341-6408-IK-2020-05-RL date de publication en ligne : 25/05/2020 En ligne : https://doi.org/10.35614/ISSN-2341-6408-IK-2020-05-RL Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95404 [article]

Documents numériques

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City-descriptive input data for urban climate models: Model requirements, data sources and challenges / Valéry Masson in Urban climate, vol 31 (March 2020)  

Public [article]  inUrban climate > vol 31 (March 2020) Titre : City-descriptive input data for urban climate models: Model requirements, data sources and challenges Type de document : Article/Communication Auteurs : Valéry Masson, Auteur ; Wieke Heldens, Auteur ; Erwan Bocher, Auteur ; Marion Bonhomme, Auteur ; Bénédicte Bucher , Auteur ; et al., Auteur Année de publication : 2020 Projets : URCLIM / Bucher, Bénédicte Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] données localisées numériques [Termes descripteurs IGN] données socio-économiques [Termes descripteurs IGN] flore urbaine [Termes descripteurs IGN] morphologie urbaine [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] ville [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed. Numéro de notice : A2020-003 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.uclim.2019.100536 date de publication en ligne : 19/11/2019 En ligne : https://doi.org/10.1016/j.uclim.2019.100536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94290 [article]

Estimation of metabolic flows of urban environment based on fuzzy expert knowledge / Igor Patrakeyev in Geodesy and cartography, vol 46 n° 1 (January 2020)  

Public [article]  inGeodesy and cartography > vol 46 n° 1 (January 2020) . - pp 8 – 16 Titre : Estimation of metabolic flows of urban environment based on fuzzy expert knowledge Type de document : Article/Communication Auteurs : Igor Patrakeyev, Auteur ; Victor Ziborov, Auteur ; Oleksii Mikhno, Auteur Année de publication : 2020 Article en page(s) : pp 8 – 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information [Termes descripteurs IGN] aménagement durable [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] environnement [Termes descripteurs IGN] logique floue [Termes descripteurs IGN] système d'information urbain [Termes descripteurs IGN] système expert flou [Termes descripteurs IGN] Ukraine [Termes descripteurs IGN] ville [Termes descripteurs IGN] zone urbaine Résumé : (auteur) The quality and comfort of the urban environment serve as one of the most important factors for ensuring the competitiveness of municipalities, regions and countries. The quality of the urban environment is determined by the qual-ity of its three components: anthropogenic, natural and social environment. The main problem of assessing the state of the urban environment is the fragmentation of methodological approaches and adequate tools for assessing the qualitative state of the urban environment. This objectively makes it difficult for municipal authorities to use this assessment as an ele-ment in the system of urban planning decision making. We have developed an intelligent information system to provide an assessment of potential, real and lost opportunities of the urban environment using fuzzy expert knowledge. This system operates in the conditions of using non-numeric, inaccurate and incomplete information to ensure the management of sustainable city development. The system for assessing the potential, real and lost opportunities of the urban environment is based on the use of fuzzy logic equations. It allows to evaluate the effectiveness of metabolic transformations of each subsystem of the urban environment. Numéro de notice : A2020-221 Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.3846/gac.2020.8560 date de publication en ligne : 27/02/2020 En ligne : https://doi.org/10.3846/gac.2020.8560 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94926 [article]

Extracting urban landmarks from geographical datasets using a random forests classifier / Yue Lin in International journal of geographical information science IJGIS, vol 33 n°12 (December 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n°12 (December 2019) . - pp 2406 - 2423 Titre : Extracting urban landmarks from geographical datasets using a random forests classifier Type de document : Article/Communication Auteurs : Yue Lin, Auteur ; Yuyang Cai, Auteur ; Yue Gong, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 2406 - 2423 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] gestion des itinéraires [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] point de repère [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] représentation mentale spatiale [Termes descripteurs IGN] saillance [Termes descripteurs IGN] Shenzhen [Termes descripteurs IGN] ville Résumé : (auteur) Urban landmarks are of significant importance to spatial cognition and route navigation. However, the current landmark extraction methods mainly focus on the visual salience of landmarks and are insufficient for obtaining high extraction accuracy when the size of the geographical dataset varies. This study introduces a random forests (RF) classifier combining with the synthetic minority oversampling technique (SMOTE) in urban landmark extraction. Both GIS and social sensing data are employed to quantify the structural and cognitive salience of the examined urban features, which are available from basic spatial databases or mainstream web service application programming interfaces (APIs). The results show that the SMOTE-RF model performs well in urban landmark extraction, with the values of recall, precision, F-measure and AUC reaching 0.851, 0.831, 0.841 and 0.841, respectively. Additionally, this method is suitable for both large and small geographical datasets. The ranking of variable importance given by this model further indicates that certain cognitive measures – such as feature class, Weibo popularity and Bing popularity – can serve as crucial factors for determining a landmark. The optimal variable combination for landmark extraction is also acquired, which might provide support for eliminating the variable selection requirement in other landmark extraction methods. Numéro de notice : A2019-426 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1620238 date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1620238 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93559 [article]

Nouvelle donne aérienne / Marielle Mayo in Géomètre, n° 2175 (décembre 2019)

Public [article]  inGéomètre > n° 2175 (décembre 2019) . - pp 12 - 13 Titre : Nouvelle donne aérienne Type de document : Article/Communication Auteurs : Marielle Mayo, Auteur Année de publication : 2019 Article en page(s) : pp 12 - 13 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] capacité de stockage [Termes descripteurs IGN] Cergy-Pontoise [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image oblique [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] stockage de données Résumé : (Auteur) Depuis 1967, l'agglomération de Cergy-Pontoise met à jour son orthophotographie. Les images obliques et les données Lidar produites par une société de géomètres-experts ouvrent la porte à de nouvelles applications. Numéro de notice : A2019-605 Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94741 [article]

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
063-2019111	SL	Revue	Centre de documentation	Revues en salle	En circulation Exclu du prêt

Cartographic delimitation of the city centre using mental sketches / Kamil Nieścioruk in Cartographic journal (the), Vol 56 n° 4 (November 2019)  

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Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne / Marcello Marini in Computers, Environment and Urban Systems, vol 78 (November 2019)  

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Pressures and threats to nature related to human activities in European urban and suburban forests / Ewa Referowska-Chodak in Forests, vol 10 n° 9 (September 2019)  

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Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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CNN-based dense image matching for aerial remote sensing images / Shunping Ji in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)  

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Multi-scale object detection in remote sensing imagery with convolutional neural networks / Zhipeng Deng in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)  

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OpenStreetMap data quality enrichment through awareness raising and collective action tools—experiences from a European project / Amin Mobasheri in Geo-spatial Information Science, vol 21 n° 3 (October 2018)  

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Spatial discontinuities, health and mobility - What do the Google's POIs and tweets tell us about Bangkok's (Thailand) structures and spatial dynamics? / Alexandre Cebeillac in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)  

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Integrating multi-agent evacuation simulation and multi-criteria evaluation for spatial allocation of urban emergency shelters / Jia Yu in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

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Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

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