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Titre : Human mobility, spatiotemporal context, and environmental health : Recent advances in approaches and methods Type de document : Monographie Auteurs : Mei-Po Kwan, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 382 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 9783039211838 9783039211845 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] alimentation
[Termes IGN] données démographiques
[Termes IGN] données GPS
[Termes IGN] données massives
[Termes IGN] données spatiotemporelles
[Termes IGN] équipement collectif
[Termes IGN] mobilité territoriale
[Termes IGN] modèle dynamique
[Termes IGN] pollution acoustique
[Termes IGN] pollution atmosphérique
[Termes IGN] santé
[Termes IGN] santé mentale
[Termes IGN] système d'information géographique
[Termes IGN] transportRésumé : (éditeur) Environmental health researchers have long used concepts like the neighborhood effect to assessing people's exposure to environmental influences and the associated health impact. However, these are static notions that ignore people's daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography. Note de contenu : 1- The uncertain geographic context problem in the analysis of the relationships between obesity and the built Environment in Guangzhou
2- Using individual GPS trajectories to explore foodscape exposure: A case
study in Beijing metropolitan area
3- Cycling for transportation in Sao Paulo city: Associations with bike paths, train and subway stations
4- Estimating vehicle fuel consumption and emissions using GPS big data
5- Real-time estimation of population exposure to PM2.5 using mobile- and station-based
big data
6- An innovative context-based crystal-growth activity space method for environmental
exposure assessment: A study using GIS and GPS trajectory data collected in chicago
7- A multilevel analysis of perceived noise pollution, geographic contexts and mental health in Beijing
8- Understanding the influence of crop residue burning on PM2.5 and PM10 concentrations in China from 2013 to 2017 using MODIS data
9- The neighborhood effect averaging problem (NEAP): An elusive confounder of the
neighborhood effect
10- Exploring the influence of built environment on car ownership and use with a spatial multilevel model: A case study of Changchun, China
11- Geographical accessibility of community health assist scheme general practitioners for the elderly population in Singapore: A case study on the elderly living in housing development board flats
12- An analytical framework for integrating the spatiotemporal dynamics of environmental context and individual mobility in exposure assessment: A study on the relationship between food environment exposures and body weight
13- Evaluating the accessibility of healthcare facilities using an integrated catchment
area approach
14- Impacts of individual daily Greenspace exposure on health based on individual activity space and structural equation modeling
15- An improved healthcare accessibility measure considering the temporal dimension and
population demand of different ages
16- Perceived environmental, individual and social factors of long-distance collective walking in cities
17- Geographic imputation of missing activity space data from ecological momentary assessment (EMA) GPS positions
18- Environmental, individual and personal goal influences on older adults’ walking in the Helsinki metropolitan area
19- Spatial accessibility to primary healthcare services by multimodal means of travel: Synthesis and case study in the city of Calgary
20- Roles of different transport modes in the spatial spread of the 2009 influenza A(H1N1) pandemic in mainland China
21- Association between the activity space exposure to parks in childhood and adolescence and cognitive aging in later lifeNuméro de notice : 25948 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.3390/books978-3-03921-184-5 En ligne : https://doi.org/10.3390/books978-3-03921-184-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96379 Projection sur l’évolution de la distribution future de la population en utilisant du Machine Learning et de la géosimulation / Julie Grosmaire (2019)
Titre : Projection sur l’évolution de la distribution future de la population en utilisant du Machine Learning et de la géosimulation Type de document : Mémoire Auteurs : Julie Grosmaire, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 27 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Français (fre) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage automatique
[Termes IGN] conteneur
[Termes IGN] Docker
[Termes IGN] données démographiques
[Termes IGN] estimation statistique
[Termes IGN] Europe (géographie politique)
[Termes IGN] modèle de simulation
[Termes IGN] réseau neuronal artificielIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) Ce rapport est le résultat d’un stage de trois mois fait à l’Université Aalborg (CPH, Danemark) dans le cadre d’une deuxième année de formation à ENSG. Le travail exécuté pendant ce stage était le développement et l’optimisation d’outils et de méthodes informatiques pour PopNet (Population Neural Network), un code permettant la prédiction et estimation des évolutions démographiques en Europe dans les siècles à venir. Ce rapport traite d’analyse, de développement, de conteneurisation et d’optimisation de logiciel ainsi que d’apprentissage automatique par réseaux neuronaux Note de contenu : Introduction
1. Généralités
1.1 Présentation de l’université
1.2 Objectifs du stage
1.3 Présentation du programme PopNet
2. Optimisation de l’installation du code existant
2.1 Installation avec Anaconda
2.2 Installation avec Docker sans la base de données
2.3 Installation avec Docker avec la base de données
3. Modifications du code
3.1 Qualification des différentes modifications
3.2 Retrait de la base de données
3.3 Optimisation du temps
3.4 Modifications du réseau neuronal
4. Résultats du stage
4.1 Comparaison des résultats de Machine Learning
4.2 Exemples de rendus
4.3 Développements futurs possibles
ConclusionNuméro de notice : 26188 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Aalborg University Copenhgen Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94142 Documents numériques
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Projection sur l’évolution de la distribution future de la population... - pdf auteurAdobe Acrobat PDF Urban growth simulations in order to represent the impacts of constructions and environmental constraints on urban sprawl / Mojtaba Eslahi (2019)
Titre : Urban growth simulations in order to represent the impacts of constructions and environmental constraints on urban sprawl Titre original : Simulations de croissance urbaine pour représenter les impacts possibles des constructions et des contraintes environnementales sur l’étalement urbain Type de document : Thèse/HDR Auteurs : Mojtaba Eslahi, Auteur ; Anne Ruas , Directeur de thèse Editeur : Champs/Marne : Université Paris-Est Année de publication : 2019 Importance : 254 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse Université Paris-Est, discipline Sciences et Technologies de l’Information Géographique en Informatique à l'IFSTTARLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] bâtiment
[Termes IGN] croissance urbaine
[Termes IGN] démographie
[Termes IGN] dynamique spatiale
[Termes IGN] étalement urbain
[Termes IGN] occupation du sol
[Termes IGN] politique publique
[Termes IGN] politique territoriale
[Termes IGN] simulation spatiale
[Termes IGN] système d'information géographique
[Termes IGN] urbanisation
[Termes IGN] utilisation du solIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The process of urbanization occurs mainly due to population growth, rural exodus to cities and life style that often induces the nearly irreversible changes. It increases the artificial lands, which affect the biodiversity, ecosystems, urban climate, and reduces land for agriculture and natural areas. The focus of this thesis is to simulate diverse urbanization scenarios in order to improve public policies decision making. To do this, the SLEUTH model is used in order to investigate the impacts of building types and environmental rules on urban sprawl. In the method used, the SLEUTH model integrates more topographic data, urban tissue and demographic data, including geographical features and the environmental constraints. The main challenge in this research is to propose different urban sprawl scenarios for different kind of environmental rules while taking into account the population demand or at least population growth estimation. The SLEUTH model is one of the well-known cellular automata simulation models, which matches the dynamic simulation of urban expansion and adapts to morphological model of the urban configuration. SLEUTH, like many other urban growth simulation methods, considers only the historical data. Although, the impacts of population growth and urban tissue are implicitly considered during the calibration phase on the historical urban maps, changes in population growth rate or in building types cannot be included in its simulations. Moreover, the SLEUTH results are limited to raster data that are difficult to interpret for decision makers. The results are some pixels on which urbanization is supposed to occur, which do not make much sense from urbanism point of view. Therefore, our research aims to diversify the simulation possibilities integrating explicitly factors of building types according to population growth and providing visual methods to view urban growth scenario results in 2D and even 3D. In order to improve the SLEUTH results, different 2D urban growth simulation scenarios have been defined based on the SLEUTH model by adding buildings type and the estimation of the population growth as urban fabric factors. Each simulation corresponds to policies that are more or less restrictive of spaces considering what these territories can accommodate as a type of building and as a global population. In addition, the simulations can help the user to protect the desired lands such as the environmental spaces from urbanization. These scenarios show the simulation capabilities of the model and make it possible to improve our understanding of an urban sprawl simulation. Three different case studies with various sizes and populations are used including Toulouse metropolitan, Saint Sulpice la Pointe and Rieucros to provide a view of the effectiveness of the proposed method on several scales. The results evaluation indicates that the proposed method makes different simulations that correspond to different land priorities and constraints. It helps to see which land can be protected (where) and how building type can be used to constrain urban sprawl (how much). A 3D representation for each prospective urban growth simulations is provided in order to facilitate the interpretation of the SLEUTH simulation and differentiate the scenarios. The findings allow having different images of the city of tomorrow for applying it to urban policies. Note de contenu : Introduction
1- Urbanization and Urban Modeling
2- Methodology and Fundamentals for Model Construction
3- Application of the Model to Diversify the Simulations of Urban Sprawl
4- Creation of Fictive 3D Buildings to Facilitate the Interpretation of Simulation Results and Differentiate Scenarios
5- Conclusion and PerspectivesNuméro de notice : 25910 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique/Modélisation et simulation : Paris-Est : 2019 Organisme de stage : Institut de Recherche en Constructibilité IRC (IFSTTAR) nature-HAL : Thèse DOI : sans En ligne : https://hal.science/tel-02493929 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95906 Fine-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)
[article]
Titre : Fine-grained prediction of urban population using mobile phone location data Type de document : Article/Communication Auteurs : Jie Chen, Auteur ; Shih-Lung Shaw, Auteur ; Feng Lu, Auteur ; Mingxiao Li, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 1770 - 1786 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par réseau neuronal
[Termes IGN] données spatiotemporelles
[Termes IGN] modèle de simulation
[Termes IGN] population urbaine
[Termes IGN] Shanghai (Chine)
[Termes IGN] trace numériqueRésumé : (Auteur) Fine-grained prediction of urban population is of great practical significance in many domains that require temporally and spatially detailed population information. However, fine-grained population modeling has been challenging because the urban population is highly dynamic and its mobility pattern is complex in space and time. In this study, we propose a method to predict the population at a large spatiotemporal scale in a city. This method models the temporal dependency of population by estimating the future inflow population with the current inflow pattern and models the spatial correlation of population using an artificial neural network. With a large dataset of mobile phone locations, the model’s prediction error is low and only increases gradually as the temporal prediction granularity increases, and this model is adaptive to sudden changes in population caused by special events. Numéro de notice : A2018-304 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1460753 Date de publication en ligne : 26/04/2018 En ligne : https://doi.org/10.1080/13658816.2018.1460753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90445
in International journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1770 - 1786[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Opening GIScience : A process-based approach / Jerry Shannon in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)
[article]
Titre : Opening GIScience : A process-based approach Type de document : Article/Communication Auteurs : Jerry Shannon, Auteur ; Kyle Walker, Auteur Année de publication : 2018 Article en page(s) : pp 1911 - 1926 Note générale : Bibliothèque Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] données démographiques
[Termes IGN] Géorgie (Etats-Unis)
[Termes IGN] participation du public
[Termes IGN] production participative
[Termes IGN] RStudio
[Termes IGN] science citoyenne
[Termes IGN] WebSIGRésumé : (Auteur) Many scholars have demonstrated growing interest in GIScience in recent years, including use of open data portals, shared code and options for open access publication. These practices have made both research and data more transparent and accessible for a broad audience. This research may be open only in a limited sense for populations without expertise in the technology and methods undergirding these data. Based on two case studies using RStudio’s Shiny web platform, we argue that a process-based approach focusing on how analysis is opened throughout the research process provides a supplementary way to define and reflect upon public facing geographic research. Reflecting upon decisions we made at key points in each case study project, we identify four key tensions inherent to work in open GIScience: standardized vs. flexible tools, expert vs. community-led design, single vs. multiple audiences and established vs. emerging metrics. Numéro de notice : A2018-308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1464167 Date de publication en ligne : 03/05/2018 En ligne : https://doi.org/10.1080/13658816.2018.1464167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90465
in International journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1911 - 1926[article]Réservation
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