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Are prominent mountains frequently mentioned in text? Exploring the spatial expressiveness of text frequency / Curdin Derungs in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Are prominent mountains frequently mentioned in text? Exploring the spatial expressiveness of text frequency Type de document : Article/Communication Auteurs : Curdin Derungs, Auteur ; Tanja Samardžić, Auteur Année de publication : 2018 Article en page(s) : pp 856 - 873 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie
[Termes IGN] Alpes centrales
[Termes IGN] échelle géographique
[Termes IGN] géomorphologie
[Termes IGN] recherche d'information géographique
[Termes IGN] Suisse
[Termes IGN] toponyme
[Termes IGN] traitement du langage naturelRésumé : (Auteur) Data-driven GIScience shows a growing interest in making spatial information from large text data. In this paper, we quantify and thus evaluate the relation between text frequency and properties of the outer-text, geographic setting by comparing text frequencies of mountain names to the respective geomorphometric characteristics. We focus on some 2000 unique mountain names that appear some 50,000 times in a large compilation of texts on Swiss alpine history. The results on the full data set suggest only a weak relation: only 5–10% of the variation in the text frequency being explained by the respective geomorphometric characteristics. However, an analysis of multiple scales allows us to identify a Simpson’s Paradox. What appears to be ‘noise’ in the analysis of all mountains in the whole of Switzerland shows significant local signals. Small spatial extents, found all over Switzerland, can show considerably strong correlations between text frequency and spatial prominence, with up to 90% of the total variation explained. We argue that our findings have practical implications for data-driven GIScience. Retrieving meaningful spatial information from text might only be possible if the spatial scale of analysis reflects the spatial scale described in the input text documents. Numéro de notice : A2018-194 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1418362 Date de publication en ligne : 26/12/2017 En ligne : https://doi.org/10.1080/13658816.2017.1418362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89859
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 856 - 873[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Volunteered geographic information quality assessment using trust and reputation modelling in land administration systems in developing countries / Kealeboga K. Moreri in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Volunteered geographic information quality assessment using trust and reputation modelling in land administration systems in developing countries Type de document : Article/Communication Auteurs : Kealeboga K. Moreri, Auteur ; David Fairbairn, Auteur ; Philip James, Auteur Année de publication : 2018 Article en page(s) : pp 931 - 959 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger
[Termes IGN] base de données foncières
[Termes IGN] données localisées des bénévoles
[Termes IGN] pays en développement
[Termes IGN] qualité des donnéesRésumé : (Auteur) This article presents an innovative approach to establish the quality and credibility of Volunteered Geographic Information (VGI) such that it can be considered in Land Administration Systems (LAS) on a Fit for Purpose (FFP) basis. A participatory land information system can provide affordable and timely FFP information about land and its resources. However, the establishment of such a system involves more than just technical solutions and administrative procedures: many social, economic and political aspects must be considered. Innovative approaches like VGI can help address the lack of accurate, reliable and FFP land information for LAS, but integration of such sources relies on the quality and credibility of VGI. Verifying volunteer efforts can be difficult without reference to ground truth: a novel Trust and Reputation Modelling methodology is proposed as a suitable technique to effect such VGI data set validation. This method has been applied to successfully demonstrate that VGI can produce accurate and reliable data sets which can be used to conduct regular systematic updates of geographic information in official systems. It relies on a view that the public can police themselves in establishing proxy measures of VGI quality thus facilitating VGI to be used on a FFP basis in LAS. Numéro de notice : A2018-195 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1409353 Date de publication en ligne : 25/01/2018 En ligne : https://doi.org/10.1080/13658816.2017.1409353 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89860
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 931 - 959[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Classifying airborne LiDAR point clouds via deep features learned by a multi-scale convolutional neural network / Ruibin Zhao in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Classifying airborne LiDAR point clouds via deep features learned by a multi-scale convolutional neural network Type de document : Article/Communication Auteurs : Ruibin Zhao, Auteur ; Mingyong Pang, Auteur ; Jidong Wang, Auteur Année de publication : 2018 Article en page(s) : pp 960 - 979 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] classification
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] régression
[Termes IGN] réseau neuronal convolutif
[Termes IGN] semis de pointsRésumé : (Auteur) Point cloud classification plays a critical role in many applications of airborne light detection and ranging (LiDAR) data. In this paper, we present a deep feature-based method for accurately classifying multiple ground objects from airborne LiDAR point clouds. With several selected attributes of LiDAR point clouds, our method first creates a group of multi-scale contextual images for each point in the data using interpolation. Taking the contextual images as inputs, a multi-scale convolutional neural network (MCNN) is then designed and trained to learn the deep features of LiDAR points across various scales. A softmax regression classifier (SRC) is finally employed to generate classification results of the data with a combination of the deep features learned from various scales. Compared with most of traditional classification methods, which often require users to manually define a group of complex discriminant rules or extract a set of classification features, the proposed method has the ability to automatically learn the deep features and generate more accurate classification results. The performance of our method is evaluated qualitatively and quantitatively using the International Society for Photogrammetry and Remote Sensing benchmark dataset, and the experimental results indicate that our method can effectively distinguish eight types of ground objects, including low vegetation, impervious surface, car, fence/hedge, roof, facade, shrub and tree, and achieves a higher accuracy than other existing methods. Numéro de notice : A2018-196 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1431840 Date de publication en ligne : 15/02/2018 En ligne : https://doi.org/10.1080/13658816.2018.1431840 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89861
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 960 - 979[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Attribute trajectory analysis : a framework to analyse attribute changes using trajectory analysis techniques / Long Zhang in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Attribute trajectory analysis : a framework to analyse attribute changes using trajectory analysis techniques Type de document : Article/Communication Auteurs : Long Zhang, Auteur ; Nico Van De Weghe, Auteur Année de publication : 2018 Article en page(s) : pp 1043 - 1059 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] attribut
[Termes IGN] mesure de similitude
[Termes IGN] objet mobile
[Termes IGN] trajectoire (véhicule non spatial)
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Trajectory analysis has attracted growing attention in the research field of geography. Beyond traditional moving object trajectories, another type of trajectory exists in which the coordinates are object attributes rather than geographical coordinates. In this paper, a framework to analyse these so-called attribute trajectories is proposed that uses four techniques typically employed in the analysis of moving object trajectories: the Reeb graph, the similarity matrix, the convoy and the mega-convoy. The Reeb graph provides the ability to visualise the temporal dynamics of attribute similarities. The similarity matrix is a supplement of the Reeb graph whose purpose is to visualise the pairwise similarities among the attributes. Moreover, the similarity matrix forms a basis for clustering. The convoy highlights objects whose attributes remain similar for a sufficiently long period. The mega-convoy reduces the number of convoys and reveals their evolutionary histories by merging overlapping convoys. A small real-world meteorological dataset is used as an example to illustrate the attribute trajectory analysis framework and the techniques. This paper aims to form a starting point for applying trajectory analysis techniques in many research fields. Numéro de notice : A2018-199 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1435885 Date de publication en ligne : 07/02/2018 En ligne : https://doi.org/10.1080/13658816.2018.1435885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89868
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1043 - 1059[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Context-aware automated interpretation of elaborate natural language descriptions of location through learning from empirical data / Kristin Stock in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Context-aware automated interpretation of elaborate natural language descriptions of location through learning from empirical data Type de document : Article/Communication Auteurs : Kristin Stock, Auteur ; Javid Yousaf, Auteur Année de publication : 2018 Article en page(s) : pp 1087 - 1116 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie
[Termes IGN] mesure de similitude
[Termes IGN] ontologie
[Termes IGN] prise en compte du contexte
[Termes IGN] raisonnement spatial
[Termes IGN] toponyme
[Termes IGN] traitement du langage naturelRésumé : (Auteur) Natural language descriptions of location can be complex, involving many different elements and often describing location by reference to other objects. Descriptions may be vague, and their meaning often depends upon the context within which the description has been expressed. Many previous approaches use mathematical models, focus on prepositions, and have had limited success and application. We present an approach to the interpretation of geospatial natural language expressions that uses a knowledge base of expressions for which human interpretations (in the form of degree of match to one of 50 geometric configurations) are known. Our approach interprets new expressions by finding the most similar knowledge base expression and adopting its meaning. We determine expression similarity using four different methods: element match; linguistic collocation approaches (Cosine); wordnet semantic network distance and a new approach that incorporates the contextual aspects of the expression including scale, geometry type, axial structure, image-schema and liquid/solid. As well as preposition, relatum and locatum, we consider spatial adjectives, adverbs, verb and sub-parts of the relatum and locatum. The method that incorporates context was the most successful of the four tested, selecting the same geometric configuration as human respondents in 69% of cases. Numéro de notice : A2018-200 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1432861 Date de publication en ligne : 07/02/2018 En ligne : https://doi.org/10.1080/13658816.2018.1432861 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89869
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1087 - 1116[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Synchronising geometric representations for map mashups using relative positioning and Linked Data / Weiming Huang in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Synchronising geometric representations for map mashups using relative positioning and Linked Data Type de document : Article/Communication Auteurs : Weiming Huang, Auteur ; Ali Mansourian, Auteur ; Ehsan Abdolmajidi, Auteur ; Haiqi Xu, Auteur ; Lars Harrie, Auteur Année de publication : 2018 Article en page(s) : pp 1117 - 1137 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] application composite
[Termes IGN] géovisualisation
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] positionnement différentiel
[Termes IGN] représentation multiple
[Termes IGN] SPARQL
[Termes IGN] synchronisation
[Termes IGN] web des donnéesRésumé : (Auteur) Map mashups, as a common way of presenting geospatial information on the Web, are generally created by spatially overlaying thematic information on top of various base maps. This simple overlay approach often raises geometric deficiencies due to geometric uncertainties in the data. This issue is particularly apparent in a multi-scale context because the thematic data seldom have synchronised level of detail with the base map. In this study, we propose, develop, implement and evaluate a relative positioning approach based on shared geometries and relative coordinates to synchronise geometric representations for map mashups through several scales. To realise the relative positioning between datasets, we adopt a Linked Data–based technical framework in which the data are organised according to ontologies that are designed based on the GeoSPARQL vocabulary. A prototype system is developed to demonstrate the feasibility and usability of the relative positioning approach. The results show that the approach synchronises and integrates the geometries of thematic data and the base map effectively, and the thematic data are automatically tailored for multi-scale visualisation. The proposed framework can be used as a new way of modelling geospatial data on the Web, with merits in terms of both data visualisation and querying. Numéro de notice : A2018-201 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1441416 Date de publication en ligne : 01/03/2018 En ligne : https://doi.org/10.1080/13658816.2018.1441416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89870
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1117 - 1137[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Exploring the sensitivity of coastal inundation modelling to DEM vertical error / Harry West in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)
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Titre : Exploring the sensitivity of coastal inundation modelling to DEM vertical error Type de document : Article/Communication Auteurs : Harry West, Auteur ; Michael Horswell, Auteur ; Nevil Quinn, Auteur Année de publication : 2018 Article en page(s) : pp 1172 - 1193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de sensibilité
[Termes IGN] erreur en altitude
[Termes IGN] estuaire
[Termes IGN] incertitude géométrique
[Termes IGN] inondation
[Termes IGN] littoral
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle numérique de surface
[Termes IGN] montée du niveau de la mer
[Termes IGN] Royaume-UniRésumé : (Auteur) As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover. Numéro de notice : A2018-203 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1444165 Date de publication en ligne : 14/03/2018 En ligne : https://doi.org/10.1080/13658816.2018.1444165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89874
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1172 - 1193[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible Gen*: 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)
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Titre : Gen*: a generic toolkit to generate spatially explicit synthetic populations Type de document : Article/Communication Auteurs : Kevin Chapuis, Auteur ; Patrick Taillandier , Auteur ; Misslin Renaud, Auteur ; Alexis Drogoul, Auteur
Année de publication : 2018 Article en page(s) : pp 1194 - 1210 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] distribution spatiale
[Termes IGN] figuration de la densité
[Termes IGN] modèle orienté agent
[Termes IGN] population urbaine
[Termes IGN] programmation par contraintes
[Termes IGN] recensement démographique
[Termes IGN] régression
[Termes IGN] Rouen
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Agent-based models tend to integrate more and more data that can deeply impact their outcomes. Among these data, the ones that deal with agent attributes and localization are particularly important, but are very difficult to collect. In order to tackle this issue, we propose a complete generic toolkit called Gen* dedicated to generating spatially explicit synthetic populations from global (census and GIS) data. This article focuses on the localization methods provided by Gen* that are based on regression, geometrical constraints and spatial distributions. The toolkit is applied for a case study concerning the generation of the population of Rouen (France) and shows the capabilities of Gen* regarding population spatialization. Numéro de notice : A2018-204 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1440563 Date de publication en ligne : 26/02/2018 En ligne : https://doi.org/10.1080/13658816.2018.1440563 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89875
in International journal of geographical information science IJGIS > vol 32 n° 5-6 (May - June 2018) . - pp 1194 - 1210[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018031 RAB Revue Centre de documentation En réserve 3L Disponible