Descripteur
Documents disponibles dans cette catégorie (2154)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Temporal transitions of demographic dot maps / Jeff Allen in International journal of cartography, vol 8 n° 2 (July 2022)
[article]
Titre : Temporal transitions of demographic dot maps Type de document : Article/Communication Auteurs : Jeff Allen, Auteur Année de publication : 2022 Article en page(s) : pp 208 - 222 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatio-temporelle
[Termes IGN] carte de répartition par points
[Termes IGN] carte interactive
[Termes IGN] distribution spatiale
[Termes IGN] données démographiques
[Termes IGN] données localisées historiques
[Termes IGN] interpolation linéaire
[Termes IGN] pauvreté
[Termes IGN] population
[Termes IGN] répartition géographique
[Termes IGN] représentation cartographique
[Termes IGN] représentation du changement
[Termes IGN] Toronto
[Termes IGN] visualisation cartographique
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Dot maps are often used to display the distributions of populations over space. This paper details a method for extending dot maps in order to visualize changes in spatial patterns over time. Specifically, we outline a selective linear interpolation procedure to encode the time range in which dots are visible on a map, which then allows for temporal queries and animation. This methodology is exemplified first by animating population growth across the United States, and second, through an interactive application showing changing poverty distributions in Toronto, Canada. Numéro de notice : A2022-920 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2021.1910184 Date de publication en ligne : 18/05/2021 En ligne : https://doi.org/10.1080/23729333.2021.1910184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102460
in International journal of cartography > vol 8 n° 2 (July 2022) . - pp 208 - 222[article]Visualising post-disaster damage on maps: a user study / Thomas Candela in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)
[article]
Titre : Visualising post-disaster damage on maps: a user study Type de document : Article/Communication Auteurs : Thomas Candela, Auteur ; Matthieu Péroche, Auteur ; Arnaud Sallaberry, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1364 - 1393 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de répartition par points
[Termes IGN] catastrophe naturelle
[Termes IGN] comportement
[Termes IGN] dommage matériel
[Termes IGN] enquête
[Termes IGN] lecture de carte
[Termes IGN] oculométrie
[Termes IGN] psychologie cognitive
[Termes IGN] représentation cartographique
[Termes IGN] sémiologie graphique
[Termes IGN] tessellation
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) The mapping of the damage caused by natural disasters is a crucial step in deciding on the actions to take at the international, national, and local levels. The large variety of representations that we have observed leads to problems of transfer and variations in analysis. In this article, we propose a representation, Regular Dot map (RD), and we compare it to 4 others routinely used to visualise post-disaster damage. Our comparison is based on a user study in which a set of participants carried out various tasks on multiple datasets using the various visualisations. We then analysed the behaviour during the experiment using three approaches: (1) quantitative analysis of user answers according to the reality on the ground, (2) quantitative analysis of user preferences in terms of perceived effectiveness and appearance, and (3) qualitative analysis of the data collected using an eye tracker. The results of this study lead us to believe that RD is the best compromise in terms of effectiveness among the various representations studied. Numéro de notice : A2022-492 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2063872 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1080/13658816.2022.2063872 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100971
in International journal of geographical information science IJGIS > vol 36 n° 7 (juillet 2022) . - pp 1364 - 1393[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2022071 SL Revue Centre de documentation Revues en salle Disponible 3D modeling method for dome structure using digital geological map and DEM / Xian-Yu Liu in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)
[article]
Titre : 3D modeling method for dome structure using digital geological map and DEM Type de document : Article/Communication Auteurs : Xian-Yu Liu, Auteur ; An-Bo Li, Auteur ; Hao Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 339 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] carte géologique
[Termes IGN] carte stratigraphique
[Termes IGN] courbe de Bézier
[Termes IGN] modèle géologique
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation 3D
[Termes IGN] structure géologiqueRésumé : (auteur) Geological maps have wide coverage with low acquisition difficulty. When other geological survey data are scarce, they are a valuable source of geological structure information for geological modeling. However, for structures with large deformation, geological map information has difficulty meeting the requirement of its 3D geological modeling. Therefore, this paper takes the dome structure as an example to explore a 3D modeling method based on geological maps, DEM and related geological knowledge. The method includes: (1) adaptively calculating the attitude of points on the stratigraphic boundaries; (2) inferring and generating the bottom boundary of the model from the attitude data of the boundary points; (3) generating the model interface constrained by Bézier curves based on the bottom boundary; (4) generating the top and bottom surfaces of the stratum; and (5) stitching each surface of the geological body to generate the final dome model. Case studies of the dome in Wulongshan in China and the Richat structure in Mauritania show that this method can build a solid model of the dome based only on geological maps and DEM data, whose morphological features are basically consistent with those embodied in the section view or the model generated by traditional methods. Numéro de notice : A2022-482 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11060339 Date de publication en ligne : 07/06/2022 En ligne : https://doi.org/10.3390/ijgi11060339 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100895
in ISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 339[article]Analysis of the land suitability for paddy fields in Tanzania using a GIS-based analytical hierarchy process / Ahmad Al-Hanbali in Geo-spatial Information Science, vol 25 n° 2 ([01/06/2022])
[article]
Titre : Analysis of the land suitability for paddy fields in Tanzania using a GIS-based analytical hierarchy process Type de document : Article/Communication Auteurs : Ahmad Al-Hanbali, Auteur ; Kenichi Shibuta, Auteur ; Bayan Alsaaideh, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 212 - 228 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] cultures irriguées
[Termes IGN] humidité du sol
[Termes IGN] précipitation
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] rizière
[Termes IGN] système d'information géographique
[Termes IGN] Tanzanie
[Termes IGN] utilisation du solRésumé : (auteur) The importance of irrigation development is considered a key factor for food security and poverty reduction because it improves crop productivity, and ensures stable expansion of agricultural production. However, irrigation development requires understanding of the available resources including the suitability of the land for agriculture. In this study, the land suitability for paddy fields was evaluated within the United Republic of Tanzania mainland by integrating the geographic information system (GIS) and analytical hierarchy process (AHP). In this study, 11 criteria based on various sources (soil type, soil drainage, soil organic carbon, soil pH, soil depth, elevation, slope, land use, topographic wetness index, temperature, and precipitation) were used. These criteria were used within the GIS-based AHP to identify the most suitable land for sustainable paddy field cultivation considering the preservation of the natural environment of forests and protected areas by examining two scenarios: rainfed condition and irrigation priority. The former ten criteria were assumed to be constant in both scenarios and were assigned the same scores, while the latter criterion (precipitation) was assigned different scores for varying amounts to plan new irrigation projects. Unsuitable land represents 72.8% of the study area, reducing the potential agriculture land (PAL) appropriate for cultivation to 27.2%. In the rainfed condition scenario, the very high and high suitability classes represent 17.6% of the total land of the study area and 64.7% of the PAL. In the irrigation priority scenario, the same classes represent 21.4% of the total land of the study area and 78.6% of the PAL. Finally, the distribution of the land suitability for both scenarios was analyzed within eight administrative irrigation zones to determine the irrigation zone with the greatest potential for paddy field cultivation. Numéro de notice : A2022-598 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2021.2004079 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.1080/10095020.2021.2004079 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101303
in Geo-spatial Information Science > vol 25 n° 2 [01/06/2022] . - pp 212 - 228[article]Assessing and mapping landslide susceptibility using different machine learning methods / Osman Orhan in Geocarto international, vol 37 n° 10 ([01/06/2022])
[article]
Titre : Assessing and mapping landslide susceptibility using different machine learning methods Type de document : Article/Communication Auteurs : Osman Orhan, Auteur ; Suleyman Sefa Bilgilioglu, Auteur ; Zehra Kaya, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2795 - 2820 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] carte thématique
[Termes IGN] classification et arbre de régression
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] effondrement de terrain
[Termes IGN] lithologie
[Termes IGN] pente
[Termes IGN] régression logistique
[Termes IGN] réseau neuronal artificiel
[Termes IGN] séparateur à vaste marge
[Termes IGN] TurquieRésumé : (auteur) The main aim of the present study was to produce and compare landslide susceptibility maps by using five machine learning techniques, namely, artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), random forest (RF) and, classification and regression tree (CART). The study area was determined as the Arhavi-Kabisre river basin, a region in which the most landslide incidents occur in Turkey. Firstly, a landslide inventory was produced by identifying a total of 252 landslides. Secondly, a total of 11 landslide conditioning factors were considered for the landslide susceptibility mapping. Subsequently, the five machine learning techniques were constructed with the help of the training dataset for the landslide susceptibility maps. Finally, the receiver operating characteristic (ROC), sensitivity, specificity, F-measure, accuracy and kappa index were applied to compare and validate the performance of the five machine learning techniques. Numéro de notice : A2022-594 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1837258 Date de publication en ligne : 30/10/2020 En ligne : https://doi.org/10.1080/10106049.2020.1837258 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101298
in Geocarto international > vol 37 n° 10 [01/06/2022] . - pp 2795 - 2820[article]How can Sentinel-2 contribute to seagrass mapping in shallow, turbid Baltic Sea waters? / Katja Kuhwald in Remote sensing in ecology and conservation, vol 8 n° 3 (June 2022)PermalinkThe promising combination of a remote sensing approach and landscape connectivity modelling at a fine scale in urban planning / Elie Morin in Ecological indicators, vol 139 (June 2022)PermalinkTowards the automated large-scale reconstruction of past road networks from historical maps / Johannes H. Uhl in Computers, Environment and Urban Systems, vol 94 (June 2022)PermalinkClassification of vegetation classes by using time series of Sentinel-2 images for large scale mapping in Cameroon / Hermann Tagne in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)PermalinkVegetation cover mapping from RGB webcam time series for land surface emissivity retrieval in high mountain areas / Benedikt Hiebl in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)PermalinkNovel hybrid models combining meta-heuristic algorithms with support vector regression (SVR) for groundwater potential mapping / A'Kif Al-Fugara in Geocarto international, vol 37 n° 9 ([15/05/2022])PermalinkResearch on automatic identification method of terraces on the Loess plateau based on deep transfer learning / Mingge Yu in Remote sensing, vol 14 n° 10 (May-2 2022)PermalinkAlternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation / Toshihiro Sakamoto in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)PermalinkFusion of optical, radar and waveform LiDAR observations for land cover classification / Huiran Jin in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)PermalinkMapping and prediction of soil organic carbon by an advanced geostatistical technique using remote sensing and terrain data / Santanu Malik in Geocarto international, vol 37 n° 8 ([01/05/2022])Permalink