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A vector field model to handle the displacement of multiple conflicts in building generalization / Tinghua Ai in International journal of geographical information science IJGIS, vol 29 n° 8 (August 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 8 (August 2015) . - pp 1310 - 1331 Titre : A vector field model to handle the displacement of multiple conflicts in building generalization Type de document : Article/Communication Auteurs : Tinghua Ai, Auteur ; Xiang Zhang, Auteur ; Qi Zhou, Auteur ; Min Yang, Auteur Année de publication : 2015 Article en page(s) : pp 1310 - 1331 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] conflit d'espace [Termes IGN] détection de conflit [Termes IGN] généralisation cartographique automatisée [Termes IGN] généralisation du bâti [Termes IGN] partition des données [Termes IGN] relation spatiale [Termes IGN] triangulation de Delaunay [Vedettes matières IGN] Généralisation Résumé : (Auteur) In map generalization, the displacement operation attempts to resolve proximity conflicts to guarantee map legibility. Owing to the limited representation space, conflicts may occur between both the same and different features under different contexts. A successful displacement should settle multiple conflicts, suppress the generation of secondary conflicts after moving some objects, and preserve the distribution patterns. The effect of displacement can be understood as a force that pushes related objects away with properties of propagation and distance decay. This study borrows the idea of vector fields from physics discipline and establishes a vector field model to handle the displacement of multiple conflicts in building generalization. A scalar field is first constructed based on a Delaunay triangulation skeleton to partition the buildings being examined (e.g., a street block). Then, we build a vector field to conduct displacement measurements through the detection of conflicts from multiple sources. The direction and magnitude of the displacement force are computed based on an iso-line model of vector field. The experiment shows that this global method can settle multiple conflicts and preserve the spatial relations and important building patterns. Numéro de notice : A2015-604 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1019886 En ligne : https://doi.org/10.1080/13658816.2015.1019886 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78025 [article]

Estimating the count of completeness errors in geographic data sets by means of a generalized Waring regression model / Francisco Javier Ariza-López in International journal of geographical information science IJGIS, vol 29 n° 8 (August 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 8 (August 2015) . - pp 1394 - 1418 Titre : Estimating the count of completeness errors in geographic data sets by means of a generalized Waring regression model Type de document : Article/Communication Auteurs : Francisco Javier Ariza-López, Auteur ; José Avila-Rodriguez, Auteur Année de publication : 2015 Article en page(s) : pp 1394 - 1418 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique [Termes IGN] Andalousie [Termes IGN] cartographie topographique [Termes IGN] erreur absolue [Termes IGN] modèle de régression Résumé : (Auteur) In this article, we propose a statistical model for estimating the probable number of completeness errors (omissions plus commissions) in a cell (a map tile or cluster) of a data set to guide updating or improvement efforts. The number of completeness errors is a count data variable related to some exogenous covariates that may also be known for each cell (e.g. count of features, rural or urban typology, etc.) and to other unknown variation sources. We propose and adjust a generalized Waring regression model for counting these errors in cells of 1 × 1 km2 on the Topographic Map of Andalusia (Spain). This model is compared with the Poisson regression model and the negative binomial regression model and performs better. The empirical relationship established by the model indicates that the number of completeness errors is related to the following exogenous covariates: the number of cartographic features of the data set, the fact that the cell covers a littoral or urban zone and the spatial division of the contracted suppliers. For cells having less than 5 errors, most of the variability corresponds to unknown external factors (liability), but when the number of errors rises, the greater part of the variability is due to unknown internal characteristics of each cell (proneness). With these estimations, the producer can derivate statistical summaries and spatial representations and develop better planning of production activities such as actualization. Numéro de notice : A2015-605 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1010536 En ligne : https://doi.org/10.1080/13658816.2015.1010536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78029 [article]

Regional dynamics of terrestrial vegetation productivity and climate feedbacks for territory of Ukraine / Dmytro Movchan in International journal of geographical information science IJGIS, vol 29 n° 8 (August 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 8 (August 2015) . - pp 1490 - 1505 Titre : Regional dynamics of terrestrial vegetation productivity and climate feedbacks for territory of Ukraine Type de document : Article/Communication Auteurs : Dmytro Movchan, Auteur ; Yuriy V. Kostyuchenko, Auteur Année de publication : 2015 Article en page(s) : pp 1490 - 1505 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique [Termes IGN] analyse en composantes principales [Termes IGN] biome [Termes IGN] changement climatique [Termes IGN] données météorologiques [Termes IGN] forêt [Termes IGN] production agricole végétale [Termes IGN] production primaire brute [Termes IGN] régression multiple [Termes IGN] steppe [Termes IGN] Ukraine [Vedettes matières IGN] Végétation et changement climatique Résumé : (Auteur) Climate change has the potential to affect terrestrial ecosystems and, thereby, the carbon cycle. Various vegetation biomes are likely to respond differently to changes in climatic factors. The purpose of this study was to analyse the trends of the terrestrial vegetation productivity and climate drivers on regional levels and relations between ones. The gross primary productivity from the global satellite-based terrestrial production efficiency model (PEM) MOD17 as the vegetation productivity indicator and meteorological data from the weather station network as climatic indicators were used. The analysis covered a period from 2000 to 2012. Correlation analysis was used to quantify the association between the vegetation productivity and climatic indicators for different growing seasons and landscape-climatic zones of Ukraine. The Mann–Kendall trend test was applied to take into account seasonal features. Multiple linear regression models for corresponding seasons and zones have been simulated using the principal component analysis. The results showed no detectable limiting effect of the climatic drivers on plant productivity for forest areas. The limiting effect of the temperature increasing and precipitation amount decreasing for the steppe zone and eastern forest-steppe subzone of Ukraine for summer was observed. Numéro de notice : A2015-606 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1051985 En ligne : https://doi.org/10.1080/13658816.2015.1051985 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78035 [article]