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Comprehensive decision-strategy space exploration for efficient territorial planning strategies / Olivier Billaud in Computers, Environment and Urban Systems, vol 83 (September 2020)  

Public [article]  inComputers, Environment and Urban Systems > vol 83 (September 2020) . - n° 101516 Titre : Comprehensive decision-strategy space exploration for efficient territorial planning strategies Type de document : Article/Communication Auteurs : Olivier Billaud, Auteur ; Maxence Soubeyrand, Auteur ; Sandra Luque, Auteur ; Maxime Lenormand, Auteur Année de publication : 2020 Article en page(s) : n° 101516 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] aménagement du territoire [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] outil d'aide à la décision [Termes descripteurs IGN] politique territoriale [Termes descripteurs IGN] pondération [Termes descripteurs IGN] service écosystémique [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] Thau (bassin de) Résumé : (auteur) GIS-based Multi-Criteria Decision Analysis is a well-known decision support tool that can be used in a wide variety of contexts. It is particularly useful for territorial planning in situations where several actors with different, and sometimes contradictory, point of views have to take a decision regarding land use development. While the impact of the weights used to represent the relative importance of criteria has been widely studied in the recent literature, the impact of the order weights used to combine the criteria have rarely been investigated. This paper presents a spatial sensitivity analysis to assess the impact of order weights determination in GIS-based Multi-Criteria Analysis by Ordered Weighted Averaging. We propose a methodology based on an efficient exploration of the decision-strategy space defined by the level of risk and trade-off in the decision process. We illustrate our approach with a land use planning process in the South of France. The objective is to find suitable areas for urban development while preserving green areas and their associated ecosystem services. The ecosystem service approach has indeed the potential to widen the scope of traditional landscape-ecological planning by including ecosystem-based benefits, including social and economic benefits, green infrastructures and biophysical parameters in urban and territorial planning. We show that in this particular case the decision-strategy space can be divided into four clusters. Each of them is associated with a map summarizing the average spatial suitability distribution used to identify potential areas for urban development. We also demonstrate the pertinence of a spatial variance within-cluster analysis to disentangle the relationship between risk and trade-off values. At the end, we perform a site suitability ranking analysis to assess the relationship between the four detected clusters. Numéro de notice : A2020-697 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2020.101516 date de publication en ligne : 04/07/2020 En ligne : https://doi.org/10.1016/j.compenvurbsys.2020.101516 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96251 [article]

NEAT approach for testing and validation of geospatial network agent-based model processes: case study of influenza spread / Taylor Anderson in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1792 - 1821 Titre : NEAT approach for testing and validation of geospatial network agent-based model processes: case study of influenza spread Type de document : Article/Communication Auteurs : Taylor Anderson, Auteur ; Suzana Dragićević, Auteur Année de publication : 2020 Article en page(s) : pp 1792 - 1821 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] agent (intelligence artificielle) [Termes descripteurs IGN] épidémie [Termes descripteurs IGN] interaction spatiale [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] outil d'aide à la décision [Termes descripteurs IGN] réseau intelligent [Termes descripteurs IGN] théorie des graphes [Termes descripteurs IGN] Vancouver (Colombie britannique) Résumé : (auteur) Agent-based models (ABM) are used to represent a variety of complex systems by simulating the local interactions between system components from which observable spatial patterns at the system-level emerge. Thus, the degree to which these interactions are represented correctly must be evaluated. Networks can be used to discretely represent and quantify interactions between system components and the emergent system structure. Therefore, the main objective of this study is to develop and implement a novel validation approach called the NEtworks for ABM Testing (NEAT) that integrates geographic information science, ABM approaches, and spatial network representations to simulate complex systems as measurable and dynamic spatial networks. The simulated spatial network structures are measured using graph theory and compared with empirical regularities of observed real networks. The approach is implemented to validate a theoretical ABM representing the spread of influenza in the City of Vancouver, Canada. Results demonstrate that the NEAT approach can validate whether the internal model processes are represented realistically, thus better enabling the use of ABMs in decision-making processes. Numéro de notice : A2020-478 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1741000 date de publication en ligne : 06/04/2020 En ligne : https://doi.org/10.1080/13658816.2020.1741000 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95625 [article]

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Suitable 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)  

Public [article]  inAnnals of GIS > vol 26 n° 2 (April 2020) . - pp 169 - 189 Titre : Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS Type de document : Article/Communication Auteurs : Dogus Guler, Auteur ; Tahsin Yomralioglu, Auteur Année de publication : 2020 Article en page(s) : pp 169 - 189 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] approche holistique [Termes descripteurs IGN] électricité [Termes descripteurs IGN] outil d'aide à la décision [Termes descripteurs IGN] pondération [Termes descripteurs IGN] processus d'analyse hiérarchisée floue [Termes descripteurs IGN] station [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] véhicule automobile [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Electric vehicles arouse interest since they not only contribute economies of countries in the context of dependency to oil but also support to more livable and sustainable urban areas. The location selection of electric vehicle charging stations is one of the most vital topics in order to enhance the use of electric vehicles. In this sense, the aim of this paper is to propose an approach that integrates Geographic Information System (GIS) techniques and Multi-Criteria Decision Making (MCDM) methods for finding suitable locations of the electric vehicle charging stations. In this regard, the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP) methods are used to calculate the weights of criteria. While the two different weights for each criterion are obtained by means of AHP in terms of environmental impact and accessibility, another weight for each criterion is obtained as a means of applying the FAHP. The intersection of three different suitability indexes is determined so as to achieve a holistic, credible result. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the alternative locations. The results show that the proposed approach offers a notable solution to be selected suitable charging station locations. Moreover, policymakers and administrators could benefit from these results in order to make efficient decisions for forward planning and strategies. Numéro de notice : A2020-322 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2020.1737226 date de publication en ligne : 09/03/2020 En ligne : https://doi.org/10.1080/19475683.2020.1737226 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95189 [article]

Distributed and parallel architectures for spatial data / Alberto Belussi (2020)  

Public Titre : Distributed and parallel architectures for spatial data Type de document : Monographie Auteurs : Alberto Belussi, Editeur scientifique ; Sara Migliorini, Editeur scientifique ; Damiano Carra, Editeur scientifique ; et al., Auteur Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 170 p. ISBN/ISSN/EAN : 978-3-03936-751-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] base de données localisées [Termes descripteurs IGN] collecte de données [Termes descripteurs IGN] développement durable [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] données massives [Termes descripteurs IGN] entrepôt de données localisées [Termes descripteurs IGN] geoportail [Termes descripteurs IGN] Hadoop [Termes descripteurs IGN] métadonnées [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] OLAP [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] PostGIS [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] SQL [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] téléphone intelligent [Termes descripteurs IGN] traitement parallèle [Termes descripteurs IGN] zone tampon Résumé : (Editeur) [Préface] In recent years, an increasing amount of spatial data has been collected by different types of devices, such as mobile phones, sensors, satellites, space telescope, and medical tools for analysis, or is generated by social networks, such as geotagged tweets. The processing of this huge amount of information, including spatial properties, which are frequently represented in heterogeneous ways, is a challenging task that has boosted research in the big data area in an attempt to investigate cases and propose new solutions for dealing with its peculiarities. In the literature, many different proposals and approaches for facing the problem have been proposed, addressing different goals and different types of users. However, most are obtained by customizing existing approaches which were originally developed for the processing of big data of the alphanumeric type, without any specific support for spatial or spatiotemporal properties. Thus, the proposed solutions can exploit the parallelism provided by these kinds of systems, but without taking into account, in a proficient way, the space and time dimensions that intrinsically characterize the analyzed datasets. As described in the literature, current solutions include: (i) the on-top approach, where an underlying system for traditional big datasets is used as a black box while spatial processing is added through the definition of user-defined functions that are specified on top of the underlying system; (ii) the from-scratch approach, where a completely new system is implemented for a specific application context; and (iii) the built-in approach, where an existing solution is extended by injecting spatial data functions into its core. This book aims at promoting new and innovative studies, proposing new architectures or innovative evolutions of existing ones, and illustrating experiments on current technologies in order to improve the efficiency and effectiveness of distributed and cluster systems when they deal with spatiotemporal data. Note de contenu : Preface 1- Distributed Processing of Location-Based Aggregate Queries Using MapReduce 2- Towards the Development of Agenda 2063 Geo-Portal to Support Sustainable Development in Africa 3- HiBuffer: Buffer Analysis of 10-Million-Scale Spatial Data in Real Time 4- Mobility DataWarehouses 5- Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC 6- LandQv2: A MapReduce-Based System for Processing Arable Land Quality Big Data 7- Mr4Soil: A MapReduce-Based Framework Integrated with GIS for Soil Erosion Modelling 8- High-Performance Geospatial Big Data Processing System Based on MapReduce Numéro de notice : 25884 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Monographie DOI : 10.3390/books978-3-03936-751-1 En ligne : https://doi.org/10.3390/books978-3-03936-751-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95762

A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy / Yan Zhou in Transactions in GIS, Vol 23 n° 5 (October 2019)  

Public [article]  inTransactions in GIS > Vol 23 n° 5 (October 2019) . - pp 1125 - 1151 Titre : A reliable traffic prediction approach for bike‐sharing system by exploiting rich information with temporal link prediction strategy Type de document : Article/Communication Auteurs : Yan Zhou, Auteur ; Yanxi Li, Auteur ; Qing Zhu, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 1125 - 1151 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] bicyclette [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] gestion prévisionnelle [Termes descripteurs IGN] New York (Etats-Unis ; ville) [Termes descripteurs IGN] regroupement de données [Termes descripteurs IGN] SOLAP [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] Washington D.C. Résumé : (auteur) Bike‐sharing systems have been widely used in major cities across the world. As bike borrowing and return at different stations in different periods are not balanced, the bikes in a bike‐sharing system need to be redistributed frequently to rebalance the system. Therefore, traffic flow forecasting of the bike‐sharing system is an important issue, as this is conducive to achieving rebalancing of the bike system. In this article, we present a new traffic flow prediction approach based on the temporal links in dynamic traffic flow networks. A station clustering algorithm is first introduced to cluster stations into groups. A temporal link prediction method based on the dynamic traffic flow network method (STW+M) is then proposed to predict the traffic flow between stations. In our method, the non‐negative tensor decomposition and time‐series analysis model capture the rich information (temporal variabilities, spatial characteristics, and weather information) of the across‐clusters transition. Then, a temporal link prediction strategy is used to forecast potential links and weights in the traffic flow network by investigating both the network structure and the results of tensor computations. In order to assess the methods proposed in this article, we have used the data of bike‐sharing systems in New York and Washington, DC to conduct bike traffic prediction and the experimental results have shown that our method produces the lowest root mean square error (RMSE) and mean square error (MSE). Compared to four prediction methods from the literature, our RMSE and MSE of the two datasets have been lowered by an average of 2.55 (Washington, DC) and 2.41 (New York) and 3.35 (Washington, DC) and 2.96 (New York), respectively. The results show that the proposed approach improves predictions of traffic flow. Numéro de notice : A2019-551 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12560 date de publication en ligne : 03/07/2019 En ligne : https://doi.org/10.1111/tgis.12560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94201 [article]

The impact of interactive visualization on trade-off-based geospatial decision-making / Goran Milutinović in International journal of geographical information science IJGIS, vol 33 n° 10 (October 2019)  

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Space, time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data / Zheye Wang in Cartography and Geographic Information Science, Vol 46 n° 4 (July 2019)  

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Exploring multiplexing tools for co-visualization in crisis units / Christelle Pierkot (2019)    

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La cartographie, ce qu'on lui fait dire / Martine Kis in Géomètre, n° 2157 (avril 2018)

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A spatio-temporal scenario model for emergency decision / Cheng Liu in Geoinformatica [en ligne], vol 22 n° 2 (April 2018)  

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Etude des usages des données 3D dans les projets d'aménagement urbain / Angela Matamoros (2018) 

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La géomatique comme aide à la décision dans le domaine de la santé / Dorothée Dumay (2018) 

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Geospatial data on the web / Linda Van Den Brink (2018)    

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GIS-based MCDA–AHP modelling for avalanche susceptibility mapping of Nubra valley region, Indian Himalaya / Satish Kumar in Geocarto international, vol 32 n° 11 (November 2017)  

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URBANSIMUL, outil web d'analyse foncière et d'aide à la décision / Bertrand Leroux in Signature, n° 64 (octobre 2017)

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