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A method for checking the quality of geographic metadata based on ISO 19157 / Manuel A. Ureña-Cámara in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 1 - 27 Titre : A method for checking the quality of geographic metadata based on ISO 19157 Type de document : Article/Communication Auteurs : Manuel A. Ureña-Cámara, Auteur ; Javier Nogueras-Iso, Auteur ; Javier Lacasta, Auteur ; Francisco Javier Ariza-López, Auteur Année de publication : 2019 Article en page(s) : pp 1 - 27 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] contrôle qualité automatique [Termes IGN] hétérogénéité sémantique [Termes IGN] interopérabilité [Termes IGN] Java (langage de programmation) [Termes IGN] métadonnées géographiques [Termes IGN] norme ISO [Termes IGN] qualité des metadonnées [Termes IGN] XML Résumé : (auteur) With recent advances in remote sensing, location-based services and other related technologies, the production of geospatial information has exponentially increased in the last decades. Furthermore, to facilitate discovery and efficient access to such information, spatial data infrastructures were promoted and standardized, with a consideration that metadata are essential to describing data and services. Standardization bodies such as the International Organization for Standardization have defined well-known metadata models such as ISO 19115. However, current metadata assets exhibit heterogeneous quality levels because they are created by different producers with different perspectives. To address quality-related concerns, several initiatives attempted to define a common framework and test the suitability of metadata through automatic controls. Nevertheless, these controls are focused on interoperability by testing the format of metadata and a set of controlled elements. In this paper, we propose a methodology of testing the quality of metadata by considering aspects other than interoperability. The proposal adapts ISO 19157 to the metadata case and has been applied to a corpus of the Spanish Spatial Data Infrastructure. The results demonstrate that our quality check helps determine different types of errors for all metadata elements and can be almost completely automated to enhance the significance of metadata. Numéro de notice : A2019-018 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1515437 Date de publication en ligne : 17/09/2018 En ligne : https://doi.org/10.1080/13658816.2018.1515437 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91675 [article]

Exemplaires(1)

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079-2019011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization / Si Song in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 134 - 154 Titre : Detecting arbitrarily shaped clusters in origin-destination flows using ant colony optimization Type de document : Article/Communication Auteurs : Si Song, Auteur ; Tao Pei, Auteur ; Ting Ma, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 134 - 154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] données localisées [Termes IGN] migration pendulaire [Termes IGN] modèle statistique [Termes IGN] optimisation par colonie de fourmis [Termes IGN] origine - destination Mots-clés libres : logarithme du rapport de vraisemblance  log likelihood ratio (LLR) Résumé : (auteur) An origin-destination (OD) flow can be defined as the movement of objects between two locations. These movements must be determined for a range of purposes, and strong interactions can be visually represented via clustering of OD flows. Identification of such clusters may be useful in urban planning, traffic planning and logistics management research. However, few methods can identify arbitrarily shaped flow clusters. Here, we present a spatial scan statistical approach based on ant colony optimization (ACO) for detecting arbitrarily shaped clusters of OD flows (AntScan_flow). In this study, an OD flow cluster is defined as a regional pair with significant log likelihood ratio (LLR), and the ACO is employed to detect the clusters with maximum LLRs in the search space. Simulation experiments based on AntScan_flow and SaTScan_flow show that AntScan_flow yields better performance based on accuracy but requires a large computational demand. Finally, a case study of the morning commuting flows of Beijing residents was conducted. The AntScan_flow results show that the regions associated with moderate- and long-distance commuting OD flow clusters are highly consistent with subway lines and highways in the city. Additionally, the regions of short-distance commuting OD flow clusters are more likely to exhibit ‘residential-area to work-area’ patterns. Numéro de notice : A2019-019 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1516287 Date de publication en ligne : 10/09/2018 En ligne : https://doi.org/10.1080/13658816.2018.1516287 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91684 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2019011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A spatiotemporal calculus for reasoning about land-use trajectories / Adeline Marinho Maciel in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 176 - 192 Titre : A spatiotemporal calculus for reasoning about land-use trajectories Type de document : Article/Communication Auteurs : Adeline Marinho Maciel, Auteur ; Gilberto Camara, Auteur ; Lubia Vinhas, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 176 - 192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Amazonie [Termes IGN] analyse diachronique [Termes IGN] analyse spatio-temporelle [Termes IGN] changement d'occupation du sol [Termes IGN] conversion [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] données maillées [Termes IGN] image Terra-MODIS [Termes IGN] Mato Grosso [Termes IGN] observation de la Terre [Termes IGN] R (langage) [Termes IGN] raisonnement spatiotemporel [Termes IGN] Relation d'Allen [Termes IGN] surveillance de la végétation [Termes IGN] temps instantané [Termes IGN] trace au sol Résumé : (auteur) Earth observation images are a powerful source of data about changes in our planet. Given the magnitude of global environmental changes taking place, it is important that Earth Science researchers have access to spatiotemporal reasoning tools. One area of particular interest is land-use change. Using data obtained from images, researchers would like to express abstractions such as ‘land abandonment’, ‘forest regrowth’, and ‘agricultural intensification’. These abstractions are specific types of land-use trajectories, defined as multi-year paths from one land cover into another. Given this need, this paper introduces a spatiotemporal calculus for reasoning about land-use trajectories. Using Allen’s interval logic as a basis, we introduce new predicates that express cases of recurrence, conversion and evolution in land-use change. The proposed predicates are sufficient and necessary to express different kinds of land-use trajectories. Users can build expressions that describe how humans modify Earth’s terrestrial surface. In this way, scientists can better understand the environmental and economic effects of land-use change. Numéro de notice : A2019-020 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1520235 Date de publication en ligne : 26/09/2018 En ligne : https://doi.org/10.1080/13658816.2018.1520235 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91685 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2019011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Automatic determination of stream networks from DEMs by using road network data to locate culverts / Ville Mäkinen in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 291 - 313 Titre : Automatic determination of stream networks from DEMs by using road network data to locate culverts Type de document : Article/Communication Auteurs : Ville Mäkinen, Auteur ; Juha Oksanen, Auteur ; Tapani Sarjakoski, Auteur ; Tapani Sarjakoski, Auteur Année de publication : 2019 Article en page(s) : pp 291 - 313 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] détection automatique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] écoulement des eaux [Termes IGN] Finlande [Termes IGN] itération [Termes IGN] modèle numérique de surface [Termes IGN] réseau hydrographique [Termes IGN] réseau routier [Termes IGN] semis de points [Termes IGN] Triangulated Irregular Network Résumé : (auteur) Determining stream networks automatically from digital elevation models is an issue that is actively being studied. The quality of elevation models has increased over time, but many hydrologically critical features, such as culverts, are often missing from the elevation data. To analyze the surficial water flow, one must either prepare a special elevation model or post-process an already-existing model. This study builds on the traditional, well-established method of determining the stream network from digital elevation models. We have extended the traditional method by locating culverts automatically, using road network data as an input. We show, by comparison to the reference data, that the culverts being most relevant for the stream network can be found with good accuracy. We demonstrate that by including the automatically located culverts in the automatic stream network determination, the quality of the generated network can be noticeably improved. Numéro de notice : A2019-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1530353 Date de publication en ligne : 11/10/2018 En ligne : https://doi.org/10.1080/13658816.2018.1530353 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91686 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2019011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Hyperparameter optimization of neural network-driven spatial models accelerated using cyber-enabled high-performance computing / Minrui Zheng in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 314 - 345 Titre : Hyperparameter optimization of neural network-driven spatial models accelerated using cyber-enabled high-performance computing Type de document : Article/Communication Auteurs : Minrui Zheng, Auteur ; Wenwu Tang, Auteur ; Xiang Zhao, Auteur Année de publication : 2019 Article en page(s) : pp 314 - 345 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] algorithme d'apprentissage [Termes IGN] analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] Caroline du Nord (Etats-Unis) [Termes IGN] données spatiotemporelles [Termes IGN] géostatistique [Termes IGN] méthode des moindres carrés [Termes IGN] modèle empirique [Termes IGN] modèle numérique de surface [Termes IGN] modélisation spatiale [Termes IGN] optimisation (mathématiques) [Termes IGN] régression linéaire [Termes IGN] réseau neuronal artificiel [Termes IGN] système d'information foncière Résumé : (auteur) Artificial neural networks (ANNs) have been extensively used for the spatially explicit modeling of complex geographic phenomena. However, because of the complexity of the computational process, there has been an inadequate investigation on the parameter configuration of neural networks. Most studies in the literature from GIScience rely on a trial-and-error approach to select the parameter setting for ANN-driven spatial models. Hyperparameter optimization provides support for selecting the optimal architectures of ANNs. Thus, in this study, we develop an automated hyperparameter selection approach to identify optimal neural networks for spatial modeling. Further, the use of hyperparameter optimization is challenging because hyperparameter space is often large and the associated computational demand is heavy. Therefore, we utilize high-performance computing to accelerate the model selection process. Furthermore, we involve spatial statistics approaches to improve the efficiency of hyperparameter optimization. The spatial model used in our case study is a land price evaluation model in Mecklenburg County, North Carolina, USA. Our results demonstrate that the automated selection approach improves the model-level performance compared with linear regression, and the high-performance computing and spatial statistics approaches are of great help for accelerating and enhancing the selection of optimal neural networks for spatial modeling. Numéro de notice : A2019-022 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1530355 Date de publication en ligne : 12/10/2018 En ligne : https://doi.org/10.1080/13658816.2018.1530355 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91689 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2019011	RAB	Revue	Centre de documentation	En réserve L003	Disponible