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A cyber-enabled spatial decision support system to inventory mangroves in Mozambique: coupling scientific workflows and cloud computing / Wenwu Tang in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 907 - 938 Titre : A cyber-enabled spatial decision support system to inventory mangroves in Mozambique: coupling scientific workflows and cloud computing Type de document : Article/Communication Auteurs : Wenwu Tang, Auteur ; Wenpeng Feng, Auteur ; Meijuan Jia, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 907 - 938 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] informatique en nuage [Termes IGN] inventaire de la végétation [Termes IGN] lever des détails [Termes IGN] mangrove [Termes IGN] modélisation [Termes IGN] Mozambique [Termes IGN] synergiciel [Termes IGN] système d'aide à la décision [Termes IGN] Zambèze (fleuve) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for integrating such a sampling design of fieldwork with operational considerations and evaluation of alternative scenarios. However, this fieldwork design driven by SDSS is often computationally intensive and repetitive. In this study, we develop a cyber-enabled SDSS framework to facilitate the computationally challenging fieldwork design that requires the efficacious selection of base camps and plots for the inventory of mangroves. Our study area is the Zambezi River Delta, Mozambique. Cyber-enabled capabilities, including scientific workflows and cloud computing, are integrated with the SDSS. Scientific workflows enable the automation of data and modeling tasks in the SDSS. Cloud computing offers on-demand computational support for interoperation among stakeholders for collaborative scenario evaluation for the fieldwork design of mangrove inventory. Further, this framework allows for harnessing high-performance computing capabilities for accelerating the fieldwork design. The cyber-enabled framework provides significant merits in terms of effective coordination among science and logistical teams, assurance of meeting inventory objectives, and an objective basis to collectively and efficaciously evaluate alternative scenarios. Numéro de notice : A2017-237 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1250900 En ligne : http://dx.doi.org/10.1080/13658816.2016.1250900 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85171 [article]

Exemplaires(1)

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079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Geographically weighted regression with parameter-specific distance metrics / Binbin Lu in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 982 - 998 Titre : Geographically weighted regression with parameter-specific distance metrics Type de document : Article/Communication Auteurs : Binbin Lu, Auteur ; Chris Brunsdon, Auteur ; Martin Charlton, Auteur ; Paul Harris, Auteur Année de publication : 2017 Article en page(s) : pp 982 - 998 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] anisotropie [Termes IGN] métrique [Termes IGN] régression géographiquement pondérée [Termes IGN] relation spatiale Résumé : (auteur) Geographically weighted regression (GWR) is an important local technique to model spatially varying relationships. A single distance metric (Euclidean or non-Euclidean) is generally used to calibrate a standard GWR model. However, variations in spatial relationships within a GWR model might also vary in intensity with respect to location and direction. This assertion has led to extensions of the standard GWR model to mixed (or semiparametric) GWR and to flexible bandwidth GWR models. In this article, we present a strongly related extension in fitting a GWR model with parameter-specific distance metrics (PSDM GWR). As with mixed and flexible bandwidth GWR models, a back-fitting algorithm is used for the calibration of the PSDM GWR model. The value of this new GWR model is demonstrated using a London house price data set as a case study. The results indicate that the PSDM GWR model can clearly improve the model calibration in terms of both goodness of fit and prediction accuracy, in contrast to the model fits when only one metric is singly used. Moreover, the PSDM GWR model provides added value in understanding how a regression model’s relationships may vary at different spatial scales, according to the bandwidths and distance metrics selected. PSDM GWR deals with spatial heterogeneities in data relationships in a general way, although questions remain on its model diagnostics, distance metric specification, and computational efficiency, providing options for further research. Numéro de notice : A2017-238 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1263731 En ligne : http://dx.doi.org/10.1080/13658816.2016.1263731 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85172 [article]

Exemplaires(1)

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079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

3D tree modeling from incomplete point clouds via optimization and L1-MST / Jie Mei in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 999 - 1021 Titre : 3D tree modeling from incomplete point clouds via optimization and L1-MST Type de document : Article/Communication Auteurs : Jie Mei, Auteur ; Liqiang Zhang, Auteur ; Shihao Wu, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 999 - 1021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme STA [Termes IGN] arbre (flore) [Termes IGN] branche (arbre) [Termes IGN] densité des points [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] méthode robuste [Termes IGN] modèle numérique d'objet [Termes IGN] optimisation (mathématiques) [Termes IGN] semis de points [Termes IGN] semis de points clairsemés [Termes IGN] squelettisation Résumé : (auteur) Reconstruction of 3D trees from incomplete point clouds is a challenging issue due to their large variety and natural geometric complexity. In this paper, we develop a novel method to effectively model trees from a single laser scan. First, coarse tree skeletons are extracted by utilizing the L1-median skeleton to compute the dominant direction of each point and the local point density of the point cloud. Then we propose a data completion scheme that guides the compensation for missing data. It is an iterative optimization process based on the dominant direction of each point and local point density. Finally, we present a L1-minimum spanning tree (MST) algorithm to refine tree skeletons from the optimized point cloud, which integrates the advantages of both L1-median skeleton and MST algorithms. The proposed method has been validated on various point clouds captured from single laser scans. The experiment results demonstrate the effectiveness and robustness of our method for coping with complex shapes of branching structures and occlusions. Numéro de notice : A2017-239 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1264075 En ligne : http://dx.doi.org/10.1080/13658816.2016.1264075 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85173 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

An 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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1022 - 1041 Titre : An intelligent spatial land use planning support system using socially rational agents Type de document : Article/Communication Auteurs : Seyed Moral Ghavami, Auteur ; Mohammad Taleai, Auteur ; Theo Arentze, Auteur Année de publication : 2017 Article en page(s) : pp 1022 - 1041 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] acteur [Termes IGN] apprentissage automatique [Termes IGN] géographie sociale [Termes IGN] négociation [Termes IGN] outil d'aide à la décision [Termes IGN] planification urbaine [Termes IGN] surveillance de l'urbanisation [Termes IGN] système multi-agents [Termes IGN] utilisation du sol Résumé : (auteur) This research presents an intelligent planning support system based on multi-agent systems for spatial urban land use planning. The proposed system consists of two main phases: a pre-negotiation phase and an automated negotiation phase. The pre-negotiation phase involves interaction between human actors and intelligent software agents in order to elicit the actors’ social preferences. The agents employ social value orientation theory, which is rooted in social psychology, in order to model actors’ social preferences. The automated negotiation phase involves negotiation among autonomous software agents, the aim being to achieve consensus about the spatial problem on behalf of the relevant actors and using the information obtained. This study employs a computationally effective Bayesian learning technique, along with social value orientation theory, to design socially rational intelligent agents who work on behalf of real actors. The proposed system is applied to a real world urban land use planning case study. Human actors participate in a pre-negotiation phase, and their social preferences are elicited by intelligent software agents through a number of interactions. Then, software agents come together to engage in an automated negotiation phase and eventually reach an agreement on the spatial configuration of urban land uses on behalf of the actors. The results of the study show that the proposed system is effective at performing an automated negotiation, plus that the final plan – which is the output of the automated negotiation – produces higher social utility and better spatial land use configurations for the agents. Numéro de notice : A2017-240 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1263306 En ligne : http://dx.doi.org/10.1080/13658816.2016.1263306 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85175 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships / Ick-Hoi Kim in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1042 - 1060 Titre : A simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships Type de document : Article/Communication Auteurs : Ick-Hoi Kim, Auteur ; Chen-Chieh Feng, Auteur ; Yi-Chen Wang, Auteur Année de publication : 2017 Article en page(s) : pp 1042 - 1060 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] appariement de données localisées [Termes IGN] axe médian [Termes IGN] base de données historiques [Termes IGN] classification par arbre de décision [Termes IGN] conflation [Termes IGN] distance de Hausdorff [Termes IGN] données anciennes [Termes IGN] objet géographique linéaire [Termes IGN] relation topologique [Termes IGN] réseau routier [Termes IGN] similitude [Termes IGN] valeur moyenne Résumé : (auteur) Linear feature matching is one of the crucial components for data conflation that sees its usefulness in updating existing data through the integration of newer data and in evaluating data accuracy. This article presents a simplified linear feature matching method to conflate historical and current road data. To measure the similarity, the shorter line median Hausdorff distance (SMHD), the absolute value of cosine similarity (aCS) of the weighted linear directional mean values, and topological relationships are adopted. The decision tree analysis is employed to derive thresholds for the SMHD and the aCS. To demonstrate the usefulness of the simple linear feature matching method, four models with incremental configurations are designed and tested: (1) Model 1: one-to-one matching based on the SMHD; (2) Model 2: matching with only the SMHD threshold; (3) Model 3: matching with the SMHD and the aCS thresholds; and (4) Model 4: matching with the SMHD, the aCS, and topological relationships. These experiments suggest that Model 2, which considers only distance, does not provide stable results, while Models 3 and 4, which consider direction and topological relationships, produce stable results with levels of accuracy around 90% and 95%, respectively. The results suggest that the proposed method is simple yet robust for linear feature matching. Numéro de notice : A2017-241 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1267736 En ligne : http://dx.doi.org/10.1080/13658816.2016.1267736 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85177 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

The analysis and measurement of building patterns using texton co-occurrence matrices / Wenhao Yu in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) Titre : The analysis and measurement of building patterns using texton co-occurrence matrices Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur ; Tinghua Ai, Auteur ; Pengcheng Liu, Auteur ; Xiaoqiang Cheng, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] données vectorielles [Termes IGN] matrice de co-occurrence [Termes IGN] métrique [Termes IGN] modèle géométrique du bâti [Termes IGN] reconnaissance de formes [Termes IGN] reconstruction 2D du bâti [Termes IGN] tessellation [Termes IGN] triangulation de Delaunay [Termes IGN] voisinage (relation topologique) Résumé : (auteur) The representation and analysis of building patterns are critical for characterizing urban scenes and making decisions in urban planning. The evaluation of building patterns is a difficult spatial analysis problem that exhibits properties of symbolization, homogeneity and regularity. Open issues in this field include the development of approaches for representing building patterns and vector-based methods for computing various pattern metrics. In the image analysis domain, there are many methods for pattern recognition (e.g., texture analysis), but there are few corresponding solutions for vector data. The aim of this research is to develop several building pattern metrics and offer a texton co-occurrence matrix (TCM)-based method to quantitatively evaluate the features of building patterns. The procedure first constructs a spatial field based on a Delaunay triangulation skeleton to partition a set of buildings into a set of tessellation cells. The tessellations of building clusters have a similar structure as image representations, in that each cell corresponds to an image pixel. We then use the texton analysis to establish a matrix to describe the tessellation structure, including the neighboring relationships and individual attribute information. Finally, a set of feature descriptors is obtained from the TCM to capture the texture-related information of building groups. Through experiments on building pattern analysis and spatial queries, we show that the results of TCM-based evaluation of building patterns are consistent with those of human cognition. Numéro de notice : A2017-242 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1265121 En ligne : http://dx.doi.org/10.1080/13658816.2016.1265121 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85178 [article]

Exemplaires(1)

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079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Exploring spatiotemporal clusters based on extended kernel estimation methods / Jay Lee in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1154 - 1177 Titre : Exploring spatiotemporal clusters based on extended kernel estimation methods Type de document : Article/Communication Auteurs : Jay Lee, Auteur ; Junfang Gong, Auteur ; Shengwen Li, Auteur Année de publication : 2017 Article en page(s) : pp 1154 - 1177 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] données spatiotemporelles [Termes IGN] estimation par noyau [Termes IGN] exploration de données géographiques [Termes IGN] groupe [Termes IGN] implémentation (informatique) [Termes IGN] infraction [Termes IGN] Ohio (Etats-Unis) [Termes IGN] système d'information géographique Résumé : (auteur) We examined three different ways to integrate spatial and temporal data in kernel density estimation methods (KDE) to identify space–time clusters of geographic events. Spatial data and time data are typically measured in different units along respective dimensions. Therefore, spatial KDE methods require special extensions when incorporating temporal data to detect spatiotemporal clusters of geographical event. In addition to a real-world data set, we applied the proposed methods to simulated data that were generated through random and normal processes to compare results of different kernel functions. The comparison is based on hit rates and values of a compactness index with considerations of both spatial and temporal attributes of the data. The results show that the spatiotemporal KDE (STKDE) can reach higher hit rates while keeping identified hotspots compact. The implementation of these STKDE methods is tested using the 2012 crime event data in Akron, Ohio, as an example. The results show that STKDE methods reveal new perspectives from the data that go beyond what can be extracted by using the conventional spatial KDE. Numéro de notice : A2017-243 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1287371 En ligne : http://dx.doi.org/10.1080/13658816.2017.1287371 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85179 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules / Yongjiu Feng in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1198 - 1219 Titre : Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules Type de document : Article/Communication Auteurs : Yongjiu Feng, Auteur Année de publication : 2017 Article en page(s) : pp 1198 - 1219 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] algorithme génétique [Termes IGN] analyse diachronique [Termes IGN] automate cellulaire [Termes IGN] base de règles [Termes IGN] changement d'utilisation du sol [Termes IGN] données GPS [Termes IGN] jointure spatiale [Termes IGN] Kiangsou (Chine) [Termes IGN] modèle de simulation [Termes IGN] prédiction [Termes IGN] régression logistique [Termes IGN] simulation [Termes IGN] zone urbaine Résumé : (auteur) A novel generalized pattern search (GPS)-based cellular automata (GPS-CA) model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that computes the difference between the observed results produced from remote-sensing images and the simulated results produced by a general CA model. GPS optimization incorporating genetic algorithms (GAs) searches for the minimum difference, i.e. the smallest accumulated residuals, in fitting the CA transition rules. The CA coefficients captured by the GPS method have clear physical meanings that are closely associated with the dynamic mechanisms of land-use change. The GPS-CA model was applied to simulate urban land-use change in Kunshan City in the Yangtze River Delta from 2000 to 2015. The results show that the GPS method had a smaller root mean squared error (0.2821) than a logistic regression (LR) method (0.5256) in fitting the CA transition rules. The GPS-CA model thus outperformed the LR-CA model, with an overall accuracy improvement of 4.7%. As a result, the GPS-CA model should be a superior tool for modeling land-use change as well as predicting future scenarios in response to different conditions to support the sustainable urban development. Numéro de notice : A2017-244 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1287368 En ligne : http://dx.doi.org/10.1080/13658816.2017.1287368 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85180 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Mapping 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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1220 - 1244 Titre : Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data Type de document : Article/Communication Auteurs : Yao Yao, Auteur ; Xiaoping Liu, Auteur ; Xia Li, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1220 - 1244 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] bâtiment [Termes IGN] Canton (Kouangtoung) [Termes IGN] cartographie statistique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] densité de population [Termes IGN] données localisées des bénévoles [Termes IGN] données massives [Termes IGN] données statistiques [Termes IGN] habitat collectif [Termes IGN] habitat urbain [Termes IGN] intégration de données [Termes IGN] point d'intérêt [Termes IGN] population urbaine [Termes IGN] répartition géographique Résumé : (auteur) Fine-scale population distribution data at the building level play an essential role in numerous fields, for example urban planning and disaster prevention. The rapid technological development of remote sensing (RS) and geographical information system (GIS) in recent decades has benefited numerous population distribution mapping studies. However, most of these studies focused on global population and environmental changes; few considered fine-scale population mapping at the local scale, largely because of a lack of reliable data and models. As geospatial big data booms, Internet-collected volunteered geographic information (VGI) can now be used to solve this problem. This article establishes a novel framework to map urban population distributions at the building scale by integrating multisource geospatial big data, which is essential for the fine-scale mapping of population distributions. First, Baidu points-of-interest (POIs) and real-time Tencent user densities (RTUD) are analyzed by using a random forest algorithm to down-scale the street-level population distribution to the grid level. Then, we design an effective iterative building-population gravity model to map population distributions at the building level. Meanwhile, we introduce a densely inhabited index (DII), generated by the proposed gravity model, which can be used to estimate the degree of residential crowding. According to a comparison with official community-level census data and the results of previous population mapping methods, our method exhibits the best accuracy (Pearson R = .8615, RMSE = 663.3250, p Numéro de notice : A2017-245 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1290252 En ligne : http://dx.doi.org/10.1080/13658816.2017.1290252 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85188 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017031	RAB	Revue	Centre de documentation	En réserve L003	Disponible