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Titre : Urban Informatics Type de document : Monographie Auteurs : Wenzhong Shi, Éditeur scientifique ; Michael F. Goodchild, Éditeur scientifique ; Michael Batty, Éditeur scientifique ; et al., Auteur Editeur : Springer Nature Année de publication : 2021 Collection : The Urban Book Series Importance : 941 p. ISBN/ISSN/EAN : 978-981-1589836-- Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Urbanisme
[Termes IGN] données massives
[Termes IGN] infrastructure urbaine de données localisées
[Termes IGN] mobilité urbaine
[Termes IGN] planification urbaine
[Termes IGN] pollution
[Termes IGN] protection civile
[Termes IGN] système d'information géographique
[Termes IGN] ville durable
[Termes IGN] ville intelligenteRésumé : (éditeur) This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity. Note de contenu : 1- Introduction
2- Dimensions of Urban Science
3- Urban Systems and ApplicationsNuméro de notice : 28559 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Monographie DOI : 10.1007/978-981-15-8983-6 En ligne : https://link.springer.com/book/10.1007/978-981-15-8983-6 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97592 Social media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? / Oliver Lock in Geo-spatial Information Science, vol 23 n° 4 (December 2020)
[article]
Titre : Social media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? Type de document : Article/Communication Auteurs : Oliver Lock, Auteur ; Christopher Pettit, Auteur Année de publication : 2020 Article en page(s) : pp 275 - 292 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] artefact
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] planification urbaine
[Termes IGN] réseau social
[Termes IGN] sentiment
[Termes IGN] Sydney (Nouvelle-Galles du Sud)
[Termes IGN] traitement du langage naturel
[Termes IGN] transport public
[Termes IGN] ville intelligenteRésumé : (auteur) We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion. Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city. With such pressures on existing public transportation systems, this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services. This research forms a case study of the use of passively collected forms of big data in cities – focusing on Sydney, Australia. Firstly, it examines social media data (Tweets) related to public transport performance. Secondly, it joins this to longitudinal big data – delay information continuously broadcast by the network over a year, thus forming hundreds of millions of data artifacts. Topics, tones, and sentiment are modeled using machine learning and Natural Language Processing (NLP) techniques. These resulting data, and models, are compared to opinions derived from a citizen survey among users. The validity of such data and models versus the intentions of users, in the context of systems that monitor and improve transport performance, are discussed. As such, key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques. Numéro de notice : A2020-787 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1815596 Date de publication en ligne : 21/09/2020 En ligne : https://doi.org/10.1080/10095020.2020.1815596 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96545
in Geo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 275 - 292[article]JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases / Angeol A. Frozza in Geoinformatica, vol 24 n° 4 (October 2020)
[article]
Titre : JS4Geo: a canonical JSON Schema for geographic data suitable to NoSQL databases Type de document : Article/Communication Auteurs : Angeol A. Frozza, Auteur ; Ronaldo dos S. Mello, Auteur Année de publication : 2020 Article en page(s) : pp 987 - 1019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données localisées
[Termes IGN] données massives
[Termes IGN] format JSON
[Termes IGN] intégration de données
[Termes IGN] interopérabilité
[Termes IGN] NoSQL
[Termes IGN] système d'information géographique
[Termes IGN] système de gestion de base de donnéesRésumé : (Auteur) The large volume and variety of data produced in the current Big Data era lead companies to seek solutions for the efficient data management. Within this context, NoSQL databases rise as a better alternative to the traditional relational databases, mainly in terms of scalability and availability of data. A usual feature of NoSQL databases is to be schemaless, i.e., they do not impose a schema or have a flexible schema. This is interesting for systems that deal with complex data, such as GIS. However, the lack of a schema becomes a problem when applications need to perform processes such as data validation, data integration, or data interoperability, as there is no pattern for schema representation in NoSQL databases. On the other hand, the JSON language stands out as a standard for representing and exchanging data in document NoSQL databases, and JSON Schema is a schema representation language for JSON documents that it is also leading to become a standard. However, it does not include spatial data types. From this limitation, this paper proposes an extension to JSON Schema, called JS4Geo, that allows the definition of schemas for geographic data. We demonstrate that JS4Geo is able to represent schemas of any NoSQL data model, as well as other standards for geographic data, like GML and KML. We also present a case study that shows how a data integration system can benefit of JS4Geo to define local schemas for geographic datasets and generate an integrated global schema. Numéro de notice : A2020-497 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00415-w Date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s10707-020-00415-w Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96118
in Geoinformatica > vol 24 n° 4 (October 2020) . - pp 987 - 1019[article]Delineating and modeling activity space using geotagged social media data / Lingqian Hu in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)
[article]
Titre : Delineating and modeling activity space using geotagged social media data Type de document : Article/Communication Auteurs : Lingqian Hu, Auteur ; Zhenhong Li, Auteur ; Xinyue Ye, Auteur Année de publication : 2020 Article en page(s) : pp 277 - 288 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] distance
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] données socio-économiques
[Termes IGN] logement
[Termes IGN] loisir
[Termes IGN] Los Angeles
[Termes IGN] quartier
[Termes IGN] réseau social
[Termes IGN] sport
[Termes IGN] Twitter
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone urbaineRésumé : (auteur) It has become increasingly important in spatial equity studies to understand activity spaces – where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users’ home location and activity locations; and second, the area covered between home and activity locations. The paper also finds significant relationship between the spatial measures of activity spaces and neighborhood spatial and socioeconomic characteristics. This research enriches the literature that aims to address spatial equity in activity spaces and demonstrates the applicability of big data in urban socio-spatial research. Numéro de notice : A2020-135 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1705187 Date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1080/15230406.2019.1705187 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94843
in Cartography and Geographic Information Science > vol 47 n° 3 (May 2020) . - pp 277 - 288[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2020031 RAB Revue Centre de documentation En réserve L003 Disponible A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data / Sheng Hu in Computers, Environment and Urban Systems, vol 80 (March 2020)
[article]
Titre : A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data Type de document : Article/Communication Auteurs : Sheng Hu, Auteur ; Zhanjun He, Auteur ; Liang Wu, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] données massives
[Termes IGN] espace urbain
[Termes IGN] extraction de données
[Termes IGN] gestion urbaine
[Termes IGN] image à haute résolution
[Termes IGN] point d'intérêt
[Termes IGN] regroupement de données
[Termes IGN] télédétection spatiale
[Termes IGN] traitement du langage naturel
[Termes IGN] Wuhan (Chine)
[Termes IGN] zone urbaineRésumé : (auteur) Many studies are in an effort to explore urban spatial structure, and urban functional regions have become the subject of increasing attention among planners, engineers and public officials. Attempts have been made to identify urban functional regions using high spatial resolution (HSR) remote sensing images and extensive geo-data. However, the research scale and throughput have also been limited by the accessibility of HSR remote sensing data. Recently, big geo-data are becoming increasingly popular for urban studies since research is still accessible and objective with regard to the use of these data. This study aims to build a novel framework to provide an alternative solution for sensing urban spatial structure and discovering urban functional regions based on emerging geo-data – points of interest (POIs) data and an embedding learning method in the natural language processing (NLP) field. We started by constructing the intraurban functional corpus using a center-context pairs-based approach. A word embeddings representation model for training that corpus was used to extract multiprototype vectors in the second step, and the last step aggregated the functional parcels based on an introduced spatial clustering method, hierarchical density-based spatial clustering of applications with noise (HDBSCAN). The clustering results suggested that our proposed framework used in this study is capable of discovering the utilization of urban space with a reasonable level of accuracy. The limitation and potential improvement of the proposed framework are also discussed. Numéro de notice : A2020-191 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2019.101442 Date de publication en ligne : 15/11/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101442 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94853
in Computers, Environment and Urban Systems > vol 80 (March 2020)[article]PermalinkPermalinkFeuilles de route de la recherche européenne sur les big geodata du passé [diaporama] / Bénédicte Bucher (2020)PermalinkPermalinkPermalinkPermalinkPermalinkOpen data, big data, décisionnel, etc. : quels impacts sur la place de l'entité SIG des collectivités ? / Mathieu Le Moal in Géomatique expert, n° 132-133 (janvier - septembre 2020)PermalinkPermalinkPermalink