Descripteur
Termes IGN > aménagement > urbanisme
urbanisme
Commentaire :
Employé pour :
Aménagement urbain, Développement urbain, Habitat (urbanisme), Planification urbaine, Ville modèle. Synonyme(s)aménagement urbainVoir aussi |
Documents disponibles dans cette catégorie (1836)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Estimating 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)
[article]
Titre : Estimating and interpreting fine-scale gridded population using random forest regression and multisource data Type de document : Article/Communication Auteurs : Yun Zhou, Auteur ; Mingguo Ma, Auteur ; Kaifang Shi, Auteur ; Zhenyu Peng, Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] cartographie urbaine
[Termes IGN] catastrophe naturelle
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] données maillées
[Termes IGN] données multisources
[Termes IGN] migration humaine
[Termes IGN] modèle numérique de surface
[Termes IGN] point d'intérêt
[Termes IGN] population urbaine
[Termes IGN] risque sanitaire
[Termes IGN] secours d'urgence
[Termes IGN] zone urbaineRésumé : (auteur) Gridded population results at a fine resolution are important for optimizing the allocation of resources and researching population migration. For example, the data are crucial for epidemic control and natural disaster relief. In this study, the random forest model was applied to multisource data to estimate the population distribution in impervious areas at a 30 m spatial resolution in Chongqing, Southwest China. The community population data from the Chinese government were used to validate the estimation accuracy. Compared with the other regression techniques, the random forest regression method produced more accurate results (R2 = 0.7469, RMSE = 2785.04 and p Numéro de notice : A2020-308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060369 Date de publication en ligne : 03/06/2020 En ligne : https://doi.org/10.3390/ijgi9060369 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95155
in ISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 18 p.[article]Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)
[article]
Titre : Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data Type de document : Article/Communication Auteurs : Rochelle Schneider dos Santos, Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme du gradient
[Termes IGN] apprentissage automatique
[Termes IGN] chaleur
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] ilot thermique urbain
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] Londres
[Termes IGN] modèle de régression
[Termes IGN] mortalité
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] politique publique
[Termes IGN] Python (langage de programmation)
[Termes IGN] régression linéaire
[Termes IGN] santé
[Termes IGN] station météorologique
[Termes IGN] température au sol
[Termes IGN] température de l'air
[Termes IGN] zone urbaineRésumé : (auteur) Urbanisation generates greater population densities and an increase in anthropogenic heat generation. These factors elevate the urban–rural air temperature (Ta) difference, thus generating the Urban Heat Island (UHI) phenomenon. Ta is used in the fields of public health and epidemiology to quantify deaths attributable to heat in cities around the world: the presence of UHI can exacerbate exposure to high temperatures during summer periods, thereby increasing the risk of heat-related mortality. Measuring and monitoring the spatial patterns of Ta in urban contexts is challenging due to the lack of a good network of weather stations. This study aims to produce a parsimonious model to retrieve maximum Ta (Tmax) at high spatio-temporal resolution using Earth Observation (EO) satellite data. The novelty of this work is twofold: (i) it will produce daily estimations of Tmax for London at 1 km2 during the summertime between 2006 and 2017 using advanced statistical techniques and satellite-derived predictors, and (ii) it will investigate for the first time the predictive power of the gradient boosting algorithm to estimate Tmax for an urban area. In this work, 6 regression models were calibrated with 6 satellite products, 3 geospatial features, and 29 meteorological stations. Stepwise linear regression was applied to create 9 groups of predictors, which were trained and tested on each regression method. This study demonstrates the potential of machine learning algorithms to predict Tmax: the gradient boosting model with a group of five predictors (land surface temperature, Julian day, normalised difference vegetation index, digital elevation model, solar zenith angle) was the regression model with the best performance (R² = 0.68, MAE = 1.60 °C, and RMSE = 2.03 °C). This methodological approach is capable of being replicated in other UK cities, benefiting national heat-related mortality assessments since the data (provided by NASA and the UK Met Office) and programming languages (Python) sources are free and open. This study provides a framework to produce a high spatio-temporal resolution of Tmax, assisting public health researchers to improve the estimation of mortality attributable to high temperatures. In addition, the research contributes to practice and policy-making by enhancing the understanding of the locations where mortality rates may increase due to heat. Therefore, it enables a more informed decision-making process towards the prioritisation of actions to mitigate heat-related mortality amongst the vulnerable population. Numéro de notice : A2020-448 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2020.102066 Date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102066 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95524
in International journal of applied Earth observation and geoinformation > vol 88 (June 2020) . - 10 p.[article]An agent-based model of public space use / Kostas Cheliotis in Computers, Environment and Urban Systems, Vol 81 (May 2020)
[article]
Titre : An agent-based model of public space use Type de document : Article/Communication Auteurs : Kostas Cheliotis, Auteur Année de publication : 2020 Article en page(s) : n° 101476 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] architecture urbaine
[Termes IGN] comportement
[Termes IGN] espace public
[Termes IGN] espace urbain
[Termes IGN] modèle orienté agent
[Termes IGN] modélisation spatiale
[Termes IGN] piéton
[Termes IGN] urbanismeRésumé : (auteur) Computational models have been described as exceptionally adept at examining the complex relationships of human and crowd behaviour, with a significant portion dedicated to investigating spatial behaviour in defined environments. Within this context, this paper presents an agent-based model (ABM) for simulating activity in public spaces at the level of the individual user. Although other ABMs of individuals' spatial activity exist, they are often found to simulate specific building-related activities, and fewer still are found to examine activity in public spaces, in a systematic manner. This research provides a generalized formalization of human spatial behaviour incorporating stationary activities and social interaction within a 3D environment, and is presented using a widely accepted framework for describing ABM, the Overview, Design Concepts, and Details (ODD) protocol. A sample study using a synthetic environment is used to demonstrate applicability, and the model is tested extensively to establish robustness. Furthermore, model output is compared to observed activity patterns in other studies of similar spaces, and simulated spatial patterns of activity are found to match those observed in real-world scenarios, providing insight into the dynamics of the processes, and highlighting the potential of this approach for studying the complexities of human spatial behaviour. Numéro de notice : A2020-696 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101476 Date de publication en ligne : 19/02/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101476 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96249
in Computers, Environment and Urban Systems > Vol 81 (May 2020) . - n° 101476[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]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2020031 RAB Revue Centre de documentation En réserve L003 Disponible Dynamic floating stations model for emergency medical services with a consideration of traffic data / Chih-Hong Sun in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)
[article]
Titre : Dynamic floating stations model for emergency medical services with a consideration of traffic data Type de document : Article/Communication Auteurs : Chih-Hong Sun, Auteur ; Chen-Yang Cheng, Auteur ; Cheng-Hui Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 15 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse des besoins
[Termes IGN] distance kilométrique
[Termes IGN] durée de trajet
[Termes IGN] géolocalisation
[Termes IGN] gestion urbaine
[Termes IGN] migration pendulaire
[Termes IGN] planification urbaine
[Termes IGN] secours d'urgence
[Termes IGN] système d'information géographique
[Termes IGN] Taipei (Taïwan)
[Termes IGN] trafic routierRésumé : (auteur) To equally distribute the workload and minimize the travel distance for fire departments, we developed a new dynamic floating stations model (DFSM) to target traffic-related emergency medical services (EMS) during peak hours. This study revealed that traffic-related EMS incidents have different characteristics to other EMS incidents. The number of floating stations was determined by the number of available ambulances at a given time. The optimum floating station location was identified by using the given capacity to establish the smallest service radius. In DFSM simulations using floating stations with a capacity of 100 and 150 EMS incidents, the result shows significant improvements in comparison to the current situation. Numéro de notice : A2020-296 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050336 Date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.3390/ijgi9050336 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95134
in ISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 15 p.[article]Mapping 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)PermalinkUrban 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)PermalinkGeocoding of trees from street addresses and street-level images / Daniel Laumer in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 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)PermalinkStreet-Frontage-Net: urban image classification using deep convolutional neural networks / Stephen Law in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)PermalinkSuitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS / Dogus Guler in Annals of GIS, vol 26 n° 2 (April 2020)PermalinkUse of automated change detection and VGI sources for identifying and validating urban land use change / Ana-Maria Olteanu-Raimond in Remote sensing, vol 12 n° 7 (April 2020)PermalinkExtracting impervious surfaces from full polarimetric SAR images in different urban areas / Sara Attarchi in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)Permalink