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Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 / Sisi Yu in Geocarto international, vol 35 n° 14 ([15/10/2020])
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Titre : Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 Type de document : Article/Communication Auteurs : Sisi Yu, Auteur ; ZengXiang Zhang, Auteur ; Fang Liu, Auteur Année de publication : 2020 Article en page(s) : pp 1511 - 1526 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] agglomération
[Termes descripteurs IGN] croissance urbaine
[Termes descripteurs IGN] delta de la rivière des perles
[Termes descripteurs IGN] données démographiques
[Termes descripteurs IGN] image DMSP-OLS
[Termes descripteurs IGN] Kouangtoung (Chine)
[Termes descripteurs IGN] prise de vue nocturne
[Termes descripteurs IGN] recensement démographique
[Termes descripteurs IGN] répartition géographique
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] surveillance de l'urbanisationRésumé : (auteur) Although numerous literatures have documented the monitoring of population distributions and dynamics for socio-economic development, environmental protection, and urban planning on different scales, little attention has been paid to long-term and multi-frequency population evolution on urban agglomeration scale, especially in non-census years. Furthermore, although multi models have been applied to population spatialization based on night-time light imagery (NLT) and census data, their accuracy needs to be further improved. Selected the Pearl River Delta (PRD), China as the study area, this work aimed to solve the aforementioned problems by constructing the residential extent extraction index (REEI) and employing the population growth theory and ‘DN density–population density’ model. Results indicated that the proposed approaches were feasible to optimize NTL products and simulate populations in both census (2000, 2010) and non-census (2005) years. Population evolution in the PRD presented distinct differences from space and over time, and mainly driven by socioeconomic development. Numéro de notice : A2020-617 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576778 date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95993
in Geocarto international > vol 35 n° 14 [15/10/2020] . - pp 1511 - 1526[article]Los Angeles as a digital place: The geographies of user‐generated content / Andrea Ballatore in Transactions in GIS, Vol 24 n° 4 (August 2020)
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Titre : Los Angeles as a digital place: The geographies of user‐generated content Type de document : Article/Communication Auteurs : Andrea Ballatore, Auteur ; Stefano de Sabbata, Auteur Année de publication : 2020 Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes descripteurs IGN] analyse spatiale
[Termes descripteurs IGN] centre urbain
[Termes descripteurs IGN] contenu généré par les utilisateurs
[Termes descripteurs IGN] distribution spatiale
[Termes descripteurs IGN] données multisources
[Termes descripteurs IGN] données socio-économiques
[Termes descripteurs IGN] exploration de données géographiques
[Termes descripteurs IGN] Foursquare
[Termes descripteurs IGN] Los Angeles
[Termes descripteurs IGN] modèle de régression
[Termes descripteurs IGN] OpenStreetMap
[Termes descripteurs IGN] participation du public
[Termes descripteurs IGN] représentation géographique
[Termes descripteurs IGN] réseau social
[Termes descripteurs IGN] réseau social géodépendant
[Termes descripteurs IGN] TwitterRésumé : (auteur) Online representations of places are becoming pivotal in informing our understanding of urban life. Content production on online platforms is grounded in the geography of their users and their digital infrastructure. These constraints shape place representation, that is, the amount, quality, and type of digital information available in a geographic area. In this article we study the place representation of user‐generated content (UGC) in Los Angeles County, relating the spatial distribution of the data to its geo‐demographic context. Adopting a comparative and multi‐platform approach, this quantitative analysis investigates the spatial relationship between four diverse UGC datasets and their context at the census tract level (about 685,000 geo‐located tweets, 9,700 Wikipedia pages, 4 million OpenStreetMap objects, and 180,000 Foursquare venues). The context includes the ethnicity, age, income, education, and deprivation of residents, as well as public infrastructure. An exploratory spatial analysis and regression‐based models indicate that the four UGC platforms possess distinct geographies of place representation. To a moderate extent, the presence of Twitter, OpenStreetMap, and Foursquare data is influenced by population density, ethnicity, education, and income. However, each platform responds to different socio‐economic factors and clusters emerge in disparate hotspots. Unexpectedly, Twitter data tend to be located in denser, more deprived areas, and the geography of Wikipedia appears peculiar and harder to explain. These trends are compared with previous findings for the area of Greater London. Numéro de notice : A2020-671 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12600 date de publication en ligne : 02/01/2020 En ligne : https://doi.org/10.1111/tgis.12600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96156
in Transactions in GIS > Vol 24 n° 4 (August 2020) . - 23 p.[article]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)
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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 / Masson, Valéry 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] villeRésumé : (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 Affiliation des auteurs : LaSTIG+Ext (2020- ) 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
in FMI's climate bulletin research letters > vol 2020 n° 1 (Spring 2020) . - pp 12 - 13[article]Documents numériques
en open access
Urban climate services ... - pdf éditeurAdobe Acrobat PDFCity-descriptive input data for urban climate models: Model requirements, data sources and challenges / Valéry Masson in Urban climate, vol 31 (March 2020)
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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 / Masson, Valéry Article en page(s) : n° 100536 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 urbaineRésumé : (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 Affiliation des auteurs : LaSTIG+Ext (2016-2019) 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
in Urban climate > vol 31 (March 2020) . - n° 100536[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)
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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 urbaineRésumé : (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 Affiliation des auteurs : non IGN 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
in Geodesy and cartography > vol 46 n° 1 (January 2020) . - pp 8 – 16[article]PermalinkExtracting 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)
PermalinkPermalinkCartographic delimitation of the city centre using mental sketches / Kamil Nieścioruk in Cartographic journal (the), Vol 56 n° 4 (November 2019)
PermalinkImmigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne / Marcello Marini in Computers, Environment and Urban Systems, vol 78 (November 2019)
PermalinkPressures 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)
PermalinkLocal 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)
PermalinkCNN-based dense image matching for aerial remote sensing images / Shunping Ji in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)
PermalinkPermalinkMulti-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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