Descripteur
Termes IGN > sciences humaines et sociales > géographie humaine
géographie humaineVoir aussi |
Documents disponibles dans cette catégorie (1043)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
Mapping population distribution from open address data: application to mainland Portugal / Nelson Mileu in Journal of maps, vol 18 n° 3 (March 2023)
![]()
[article]
Titre : Mapping population distribution from open address data: application to mainland Portugal Type de document : Article/Communication Auteurs : Nelson Mileu, Auteur ; Margarida Queirós, Auteur ; Paolo Morgado, Auteur Année de publication : 2023 Article en page(s) : pp 585 - 593 Note générale : bilbliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] base de données d'adresses
[Termes IGN] carte thématique
[Termes IGN] distribution spatiale
[Termes IGN] grille
[Termes IGN] planification urbaine
[Termes IGN] population
[Termes IGN] Portugal
[Termes IGN] QGISRésumé : (auteur) Mapping population distribution remains a common need in various fields of studies. Several approaches and methodologies have been adopted to obtain high-resolution population distribution grids. The use of addresses data to obtain gridded population distribution maps emerges as one of the more recent and accurate approaches. The increasing dissemination and availability of geo-data and more specifically address data allow us to obtain updated, granular and high spatial resolution population distribution maps. This paper describes a bottom-up open addresses data mapping-based approach of gridded population distribution with a fine spatial resolution. Through a QGIS plugin, an adaptation of the housing unit methodology was implemented to obtain 500 m × 500 and 250 m × 250 m population grids for mainland Portugal. The results showed that the use of reliable addresses databases can generate gridded population distribution maps with a high degree of adjustment to reality. Numéro de notice : A2023-154 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2022.2114862 Date de publication en ligne : 07/09/2022 En ligne : https://doi.org/10.1080/17445647.2022.2114862 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102839
in Journal of maps > vol 18 n° 3 (March 2023) . - pp 585 - 593[article]BIM et enjeux climatiques, ch. City Information Modelling pour des aménagements sobres et durables : potentiel du CIM pour calculer l’intensité urbaine / Adeline Deprêtre (2023)
![]()
Titre de série : BIM et enjeux climatiques, ch Titre : City Information Modelling pour des aménagements sobres et durables : potentiel du CIM pour calculer l’intensité urbaine Type de document : Chapitre/Contribution Auteurs : Adeline Deprêtre, Auteur ; Florence Jacquinod , Auteur ; Bruno Barroca, Auteur ; Vincent Becue, Auteur
Editeur : Paris : Eyrolles Année de publication : 2023 Conférence : EduBIM 2022, 8e édition des Journées de l'enseignement et de la recherche autour du BIM et de la maquette numérique 29/11/2022 30/11/2022 Champs-sur-Marne France programme Importance : pp ISBN/ISSN/EAN : 978-2-416-00841-2 Note générale : bibliographie
Projet E3SLangues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] densité de population
[Termes IGN] format Industry foudation classes IFC
[Termes IGN] impact sur l'environnement
[Termes IGN] planification urbaine
[Termes IGN] urbanismeRésumé : (auteur) Les analyses urbaines font partie des méthodes déployées afin de tendre vers un urbanisme durable, diminuant l’impact de la construction et de la planification sur les ressources. Dans cet article nous proposons d’explorer le potentiel des City Information Models (CIM) pour étudier l’intensité urbaine à l’échelle d’un quartier, prenant en considération plusieurs paramètres contribuant à ses impacts environnementaux. Nous utilisons pour cela les premières versions du CIM du quartier La Vallée, actuellement en cours de construction. Nous exposons notre méthode expérimentale compatible avec le format ouvert IFC afin de pouvoir reproduire la démarche sur d’autres quartiers. Nous présentons ensuite une partie de nos résultats sur l’exploitation du CIM pour l’évaluation de l’intensité urbaine en phase conception. Enfin, nous proposons diverses préconisations afin de faciliter la constitution de CIM aisément mobilisables pour les analyses urbaines, mais également pour d’autres types d’analyses pouvant contribuer à la conception ou au réaménagement de quartiers en limitant leurs impacts environnementaux. Numéro de notice : H2023-001 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/URBANISME Nature : Chapître / contribution En ligne : https://hal.science/hal-04061004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102988 A comparative assessment of the statistical methods based on urban population density estimation / Merve Yılmaz in Geocarto international, vol 38 n° 1 ([01/01/2023])
![]()
[article]
Titre : A comparative assessment of the statistical methods based on urban population density estimation Type de document : Article/Communication Auteurs : Merve Yılmaz, Auteur Année de publication : 2023 Article en page(s) : n° 2152494 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] planification urbaine
[Termes IGN] population urbaine
[Termes IGN] régression géographiquement pondérée
[Termes IGN] régression multiple
[Termes IGN] TurquieRésumé : (auteur) Population density is important spatial information for addressing the use and access to land resources in cities under the Sustainable Development Goals. This is because the spatial data support appropriate spatial policies at the spatial scale and predicts how much land will be consumed in the future. The study aims to compare and evaluate the regression tools in the context of estimating the population density difference. The three analysis tools used are Random Forest-Based Classification, Multiple Linear Regression, and Geographically Weighted Regression. The sampling area covers cities around Türkiye. Comparative results showed that the two most important descriptive variables in the Random Forest-Based Classification model are the density difference of the new developed area and the connectivity. The three main explanatory variables of the Multiple Linear Regression model are centrality, vehicle ownership, and accessibility. The results of the Multiple Linear Regression model (a non-spatial model) and the Geographically Weighted Regression model (a spatial model), were found to be quite similar. The importance of accessibility and connectivity is more evident in the Multiple Linear Regression model when the Random Forest-Based Classification model highlights the density values in the new development areas. Numéro de notice : A2023-055 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2152494 Date de publication en ligne : 28/12/2022 En ligne : https://doi.org/10.1080/10106049.2022.2152494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102388
in Geocarto international > vol 38 n° 1 [01/01/2023] . - n° 2152494[article]Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population / Heng Wan in Computers, Environment and Urban Systems, vol 99 (January 2023)
![]()
[article]
Titre : Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population Type de document : Article/Communication Auteurs : Heng Wan, Auteur ; Jim Yoon, Auteur ; Vivek Srikrishnan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] carte thématique
[Termes IGN] densité de population
[Termes IGN] distribution spatiale
[Termes IGN] Etats-Unis
[Termes IGN] indicateur paysager
[Termes IGN] interpolation
[Termes IGN] occupation du sol
[Termes IGN] paysage
[Termes IGN] planification urbaine
[Termes IGN] réduction d'échelleRésumé : (auteur) Population downscaling and interpolation methods are required to produce data which correspond to spatial units used in urban planning, demography, and environmental modeling. Population data are typically aggregated at census enumeration units, which can have arbitrary, temporally-evolving boundaries. Previous approaches to imperviousness-based dasymetric mapping ignore cell-level patterning of imperviousness within a spatial unit of prediction, which potentially serve as a strong indicator of population. Landscape metrics derived from imperviousness data offer a promising approach to capture these patterns. In this study, we incorporate landscape metrics derived from impervious cover percentage maps into intelligent dasymetric mapping to downscale population from census tracts to block groups in four states with varying population densities: Connecticut, South Carolina, West Virginia, and New Mexico. We compare the performance of the landscape metrics-based models against two baseline models in all four states across three different time periods. The results show that intelligent dasymetric mapping using landscape metrics generally outperforms the two baseline models. We further compare the performance of landscape metrics as an ancillary source of information for dasymetric mapping against other traditionally-used datasets (e.g., land use, roads, nighttime lights data) in three states (Connecticut, South Carolina, and New Mexico) in 2000. We find that class area, landscape shape index, and number of patches consistently achieve lower error rates than other ancillary datasets in all the three states. Numéro de notice : A2023-013 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101899 Date de publication en ligne : 02/11/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101899 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102130
in Computers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101899[article]From data to narratives: Scrutinising the spatial dimensions of social and cultural phenomena through lenses of interactive web mapping / Tian Lan in Journal of Geovisualization and Spatial Analysis, vol 6 n° 2 (December 2022)
![]()
[article]
Titre : From data to narratives: Scrutinising the spatial dimensions of social and cultural phenomena through lenses of interactive web mapping Type de document : Article/Communication Auteurs : Tian Lan, Auteur ; Oliver O'Brien, Auteur ; James Cheshire, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] carte interactive
[Termes IGN] cartographie sensible
[Termes IGN] culture
[Termes IGN] données démographiques
[Termes IGN] données socio-économiques
[Termes IGN] impact social
[Termes IGN] récit
[Termes IGN] Royaume-Uni
[Termes IGN] sciences sociales
[Termes IGN] web mappingMots-clés libres : narrative mapping Résumé : (auteur) Modern web mapping techniques have enhanced the storytelling capability of cartography. In this paper, we present our recent development of a web mapping facility that can be used to extract interesting stories and unique insights from a diverse range of socio-economic and demographic variables and indicators, derived from a variety of datasets. We then use three curated narratives to show that online maps are effective ways of interactive storytelling and visualisation, which allow users to tailor their own story maps. We discuss the reasons for the revival of the recent attention to narrative mapping and conclude that our interactive web mapping facility powered by data assets can be employed as an accessible and powerful toolkit, to identify geographic patterns of various social and economic phenomena by social scientists, journalists, policymakers, and the public. Numéro de notice : A2022-541 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-022-00117-x Date de publication en ligne : 16/06/2022 En ligne : https://doi.org/10.1007/s41651-022-00117-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101105
in Journal of Geovisualization and Spatial Analysis > vol 6 n° 2 (December 2022) . - n° 22[article]Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators / Luis Izquierdo-Horna in Computers, Environment and Urban Systems, vol 96 (September 2022)
PermalinkMeasuring COVID-19 vulnerability for Northeast Brazilian municipalities: Social, economic, and demographic factors based on multiple criteria and spatial analysis / Ciro José Jardim De Figueiredo in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)
PermalinkUse of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)
PermalinkCan machine learning improve small area population forecasts? A forecast combination approach / Irina Grossman in Computers, Environment and Urban Systems, vol 95 (July 2022)
PermalinkTemporal transitions of demographic dot maps / Jeff Allen in International journal of cartography, vol 8 n° 2 (July 2022)
PermalinkMapping monthly population distribution and variation at 1-km resolution across China / Zhifeng Cheng in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)
PermalinkSpatial modeling of migration using GIS-based multi-criteria decision analysis: A case study of Iran / Naeim Mijani in Transactions in GIS, vol 26 n° 2 (April 2022)
PermalinkDynamic 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)
PermalinkPermalinkModelling spatial processes in quantitative human geography / A. Stewart Fotheringham in Annals of GIS, vol 28 n° 1 (January 2022)
PermalinkA square-grid sampling support to reconcile systematicity and adaptivity in the periodic spatial survey of natural resources / Olivier Bouriaud (2022)
PermalinkConnecting family trees to construct a population-scale and longitudinal geo-social network for the U.S. / Caglar Koylu in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)
PermalinkThe geography of social media data in urban areas: Representativeness and complementarity / Alvaro Bernabeu-Bautista in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)
PermalinkSpatial interpolation of mobile positioning data for population statistics / Anto Aasa in Journal of location-based services, vol 15 n° 4 ([01/10/2021])
PermalinkDevelopment of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)
PermalinkGIS-based logic scoring of preference method for urban densification suitability analysis / Shuoge Shen in Computers, Environment and Urban Systems, vol 89 (September 2021)
PermalinkReconsidering movement and exposure: Towards a more dynamic health geography / Malcolm Campbell in Geography compass, vol 15 n° 6 (June 2021)
PermalinkPermalinkGridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates / Franz Schug in Plos one, vol 16 n° 3 (March 2021)
PermalinkGeographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling / Stefanos Georganos in Geocarto international, vol 36 n° 2 ([01/02/2021])
PermalinkPopulation dynamics and natural hazard risk management: conceptual and practical linkages for the case of Austrian policy making / Christoph Clar in Natural Hazards, Vol 105 n° 2 (January 2021)
PermalinkDevelopment and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors / Marta Sapena Moll (2021)
PermalinkLocal fuzzy geographically weighted clustering: a new method for geodemographic segmentation / George Grekousis in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)
PermalinkSpatiotemporal patterns of urbanization during the last four decades in Switzerland and their impacts on urban heat islands / Marti Bosch Padros (2021)
PermalinkExploring the heterogeneity of human urban movements using geo-tagged tweets / Ding Ma in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)
PermalinkMonitoring population dynamics in the Pearl River Delta from 2000 to 2010 / Sisi Yu in Geocarto international, vol 35 n° 14 ([15/10/2020])
PermalinkA spatio-temporal web-application for the understanding of the formation of the Parisian metropolis / Emile Blettery in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol VI-4/W1 ([03/09/2020])
PermalinkImpact of extreme weather events on urban human flow: A perspective from location-based service data / Zhenhua Chen in Computers, Environment and Urban Systems, vol 83 (September 2020)
PermalinkExploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique / Hao Li in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
PermalinkLanduse and land cover identification and disaggregating socio-economic data with convolutional neural network / Jingtao Yao in Geocarto international, vol 35 n° 10 ([01/08/2020])
PermalinkEstimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)
PermalinkExtracting activity patterns from taxi trajectory data: a two-layer framework using spatio-temporal clustering, Bayesian probability and Monte Carlo simulation / Shuhui Gong in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)
PermalinkFine-scale dasymetric population mapping with mobile phone and building use data based on grid Voronoi method / Zhenzhong Peng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)
PermalinkMapping urban grey and green structures for liveable cities using a 3D enhanced OBIA approach and vital statistics / E. Banzhaf in Geocarto international, vol 35 n° 6 ([01/05/2020])
PermalinkA method for urban population density prediction at 30m resolution / Krishnachandran Balakrishnan in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)
PermalinkA review of assessment methods for cellular automata models of land-use change and urban growth / Xiaohua Tong in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)
PermalinkA global analysis of cities’ geosocial temporal signatures for points of interest hours of operation / Kevin Sparks in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)
PermalinkAn IEEE value loop of human-technology collaboration in geospatial information science / Liqiu Meng in Geo-spatial Information Science, vol 23 n° 1 (March 2020)
PermalinkRoad network structure and ride-sharing accessibility: A network science perspective / Mingshu Wang in Computers, Environment and Urban Systems, vol 80 (March 2020)
PermalinkInteractive display of surnames distributions in historic and contemporary Great Britain / Justin Van Dijk in Journal of maps, vol 16 n° 1 ([02/01/2020])
PermalinkAnalyse de la distribution spatiale des implantations humaines : apports et limites d’indicateurs multi-échelles et trans-échelles / François Sémécurbe (2020)
PermalinkArticuler cognition spatiale et cognition environnementale pour saisir les représentations socio-cognitives de l'espace / Thierry Ramadier in Revue internationale de géomatique, vol 30 n° 1-2 (janvier - juin 2020)
PermalinkPermalinkRevealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data / Yi Shi in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)
PermalinkPermalinkTrajectoires paysagères des cônes de déjection torrentiels des Alpes du nord (Maurienne et Tarentaise) / Thérèse Hugerot (2020)
PermalinkHuman Geography, Indigenous Mapping, and the US Military: A Response to Kelly and Others’ “From Cognitive Maps to Transparent Static Web Maps” / Joel Wainwright in Cartographica, vol 54 n° 4 (Winter 2019)
PermalinkMeasuring differential access to facilities between population groups using spatial Lorenz curves and related indices / Gordon A. Cromley in Transactions in GIS, Vol 23 n° 6 (November 2019)
PermalinkHigh‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)
PermalinkUnderstanding demographic and socioeconomic biases of geotagged Twitter users at the county level / Jiang Juqin in Cartography and Geographic Information Science, vol 46 n° 3 (May 2019)
PermalinkA methodology with a distributed algorithm for large-scale trajectory distribution prediction / QiuLei Guo in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)
PermalinkPermalinkPermalinkPermalinkProjection sur l’évolution de la distribution future de la population en utilisant du Machine Learning et de la géosimulation / Julie Grosmaire (2019)
PermalinkPermalinkUrban growth simulations in order to represent the impacts of constructions and environmental constraints on urban sprawl / Mojtaba Eslahi (2019)
PermalinkFine-grained prediction of urban population using mobile phone location data / Jie Chen in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
PermalinkOpening GIScience : A process-based approach / Jerry Shannon in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
PermalinkPermalinkSpatial mining of migration patterns from web demographics / T. Edwin Chow in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
PermalinkA two-stage estimation method with bootstrap inference for semi-parametric geographically weighted generalized linear models / Dengkui Li in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
PermalinkTesting time-geographic density estimation for home range analysis using an agent-based model of animal movement / Joni A. Downs in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)
PermalinkGen*: a generic toolkit to generate spatially explicit synthetic populations / Kevin Chapuis in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
PermalinkMapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records / Zhang Liu in Transactions in GIS, vol 22 n° 2 (April 2018)
PermalinkPermalinkPermalinkPermalinkResearches about the living condition in Ulaanbaatar with mapping developments based on a participatory approach / Paul Roux (2018)
PermalinkVers une nouvelle approche pour calculer les indicateurs de la densité urbaine via l'imagerie de satellite Alsat-2A / Tarek Medjadj in Bulletin des sciences géographiques, n° 31 (2017 - 2018)
PermalinkUse of unsupervised classification for the determination of prevailing land use typology / Miha Konjar in Geodetski vestnik, vol 61 n° 4 (December 2017 - February 2018)
PermalinkSocial Distance metric: from coordinates to neighborhoods / Vagan Terziyan in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)
PermalinkMapping theories of transformative learning / Daniel Casebeer in Cartographica, vol 52 n° 3 (Fall 2017)
PermalinkDepicting urban boundaries from a mobility network of spatial interactions : a case study of Great Britain with geo-located Twitter data / Junjun Yin in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
PermalinkCode Grey : mapping healthcare service deserts in Hamilton, Ontario and the impact on senior populations / Kristin M. Dosen in Cartographica, vol 52 n° 2 (Summer 2017)
PermalinkAn intelligent spatial land use planning support system using socially rational agents / Seyed Moral Ghavami in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)
PermalinkMapping fine-scale population distributions at the building level by integrating multisource geospatial big data / Yao Yao in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)
PermalinkImproving large area population mapping using geotweet densities / Nirav N. Patel in Transactions in GIS, vol 21 n° 2 (April 2017)
PermalinkEngaging indigenous people as geo-crowdsourcing sensors for ecotourism mapping via mobile data collection: a case study of the Royal Belum State Park / Nurul Hawani Idris in Cartography and Geographic Information Science, Vol 44 n° 2 (March 2017)
PermalinkInferring spatial scale change in an isopleth map / J. Lin in Cartographic journal (the), Vol 54 n° 1 (February 2017)
PermalinkDéveloppement d'un outil cartographique dasymétrique pour la modélisation de la répartition de densité de population / Safa Fennia (2017)
PermalinkRedistribution population data across a regular spatial grid according to buildings characteristics / Beata Calka in Geodesy and cartography, vol 65 n° 2 (December 2016)
PermalinkASSURE : a model for the simulation of urban expansion and intra-urban social segregation / Karolien Vermeiren in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)
PermalinkCharacterizing European urban settlements from population data : a cartographic approach / David Serano Giné in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)
PermalinkDiffuser une alerte aux crues rapides via une application smartphone en France. De la théorie à la mise en pratique / Sekedoua Kouadio in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 21 n° 4 (juillet - août 2016)
PermalinkÉvolution spatiotemporelle de l’exposition humaine face au tsunami à Padang : diagnostic de la vulnérabilité et des capacités d’évacuations à l’échelle infra-urbaine / Henky Mayaguezz in Revue internationale de géomatique, vol 26 n° 3 (juillet - septembre 2016)
PermalinkSpace-time multiple regression model for grid-based population estimation in urban areas / Ko Ko Lwin in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
PermalinkIntegrating geo web services for a user driven exploratory analysis / Simon Moncrieff in ISPRS Journal of photogrammetry and remote sensing, vol 114 (April 2016)
PermalinkElaboration d’un zonage de tissus urbains : introduire de la structure dans un référentiel carroyé / Johanna Baro in Revue internationale de géomatique, vol 26 n° 1 (janvier - mars 2016)
PermalinkLa ville à l’échelle de l’Europe : apports du couplage et de l’expertise de bases de données issues de l’imagerie satellitale / Anne Bretagnolle in Revue internationale de géomatique, vol 26 n° 1 (janvier - mars 2016)
PermalinkGeo-temporal Twitter demographics / Paul A. Longley in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)
PermalinkPermalinkExploring the impact of dasymetric refinement on spatiotemporal small area estimates / Barbara P. Buttenfield in Cartography and Geographic Information Science, Vol 42 n° 5 (November 2015)
PermalinkUtilisation des technologies géospatiales pour l'évaluation des transformations spatiales dues aux pressions anthropiques dans le canton Afféma (Sud-est ivoirien) / Armand Kangah in Photo interprétation, European journal of applied remote sensing, vol 51 n° 3 (septembre 2015)
PermalinkImportance of 3D visualization for land use planning, construction and management of the Karsıyaka settlement area (Izmir-Turkey) / Mehmet Ozcelik in International journal of 3-D information modeling, vol 4 n° 3 (July - September 2015)
Permalink