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A methodology for producing realistic hill-shading map based on shaded relief map, digital orthophotographic map fusion and IHS transformation / Hongyun Zeng in Annals of GIS, vol 27 n° 4 (December 2021)  

Public [article]  inAnnals of GIS > vol 27 n° 4 (December 2021) . - pp 371 - 382 Titre : A methodology for producing realistic hill-shading map based on shaded relief map, digital orthophotographic map fusion and IHS transformation Type de document : Article/Communication Auteurs : Hongyun Zeng, Auteur ; Zhiqiang Xie, Auteur ; Jinqu Zhang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 371 - 382 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] données vectorielles [Termes IGN] effet d'ombre [Termes IGN] espace colorimétrique [Termes IGN] géomorphologie [Termes IGN] modèle numérique de surface [Termes IGN] ombre [Termes IGN] orthophotocarte [Termes IGN] représentation du relief [Termes IGN] teinte hypsométrique [Termes IGN] transformation intensité-teinte-saturation Résumé : (auteur) The traditional hill-shading map is usually produced from a digital elevation model (DEM) by using the method of hypsometric tinting, which is capable of demonstrating the changes in geomorphology by setting the colors for hill-shading. However, the disadvantage is obvious that the surface features of the terrain can only be utilized by putting vector data on the map. Hence, the terrain display effect will be altered, especially in the production of large-scale maps, for which the artistic effect will be greatly weakened. This paper proposes a solution to this problem. First, we transform the RGB color space of the Digital orthophotographic map (DOM) image into the intensity-hue-saturation (IHS) color space. Then, we calculate the new value of the intensity as I′ for each pixel of the shaded relief model (SRM) of the high-resolution remote sensing image. Finally, we replace the component I with the new component I′ and then proceed with the inverse IHS transform. The case study shows that an objective representation of the actual situation is presented in the mapping area, and the 3D performance capabilities are enhanced. This research indicates that when the method of fusing the processed SRM with the IHS color system is used, the optimum index factor (OIF) and entropy of the generated map are 41.26 and 12.05, respectively, which are much greater than for the results of the traditional method. In other words, the proposed method can greatly enhance the terrain effect. Numéro de notice : A2021-667 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475683.2021.1921026 Date de publication en ligne : 04/05/2021 En ligne : https://doi.org/10.1080/19475683.2021.1921026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98816 [article]

Complexity-based matching between image resolution and map scale for multiscale image-map generation / Qian Peng in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 10 (October 2021) . - pp 1951 - 1974 Titre : Complexity-based matching between image resolution and map scale for multiscale image-map generation Type de document : Article/Communication Auteurs : Qian Peng, Auteur ; Zhilin Li, Auteur ; Jun Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1951 - 1974 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement de lignes [Termes IGN] échelle cartographique [Termes IGN] Hong-Kong [Termes IGN] niveau de détail [Termes IGN] objet géographique linéaire [Termes IGN] orthophotocarte [Termes IGN] précision cartographique [Termes IGN] précision planimétrique [Termes IGN] résolution globale (imagerie) [Termes IGN] symbole graphique [Termes IGN] visualisation multiéchelle [Vedettes matières IGN] Généralisation Résumé : (auteur) An image-map is a compromise between an image and a map. The quality of such maps is affected by several factors, such as (a) the matching between the features on images and the graphic symbols from maps, (b) the complexity of background images, and (c) the representation of graphic and text symbols on the images. This project deals with the first issue. The current solution is that the accuracy of images should satisfy the accuracy standard of maps. However, images with different resolutions can satisfy the standard for a specific map scale. This may lead to a situation in which the levels of detail (LoD) in images may not match the complexity of map features although the planimetric accuracy is matched. To solve this problem, we developed a complexity-based matching between the image resolution and map scale. More precisely, the matching is based on the complexity of line features. Experimental evaluations were conducted in 15 representative areas in Hong Kong using maps at seven scales and eight image resolutions. Results show that the proposed complexity-based method is capable of obtaining good matching between image resolution and map scale in terms of both accuracy and users’ preference. Numéro de notice : A2021-655 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1885674 Date de publication en ligne : 12/04/2021 En ligne : https://doi.org/10.1080/13658816.2021.1885674 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98391 [article]

Developing reliably distinguishable color schemes for legends of natural resource taxonomy-based maps / Virgil Vlad in Cartography and Geographic Information Science, Vol 48 n° 5 (September 2021)  

Public [article]  inCartography and Geographic Information Science > Vol 48 n° 5 (September 2021) . - pp 393 - 416 Titre : Developing reliably distinguishable color schemes for legends of natural resource taxonomy-based maps Type de document : Article/Communication Auteurs : Virgil Vlad, Auteur ; Mihai Toti, Auteur ; Sorina Dumitru, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 393 - 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] carte d'occupation du sol [Termes IGN] colorimétrie [Termes IGN] couleur (rédaction cartographique) [Termes IGN] couleur primaire [Termes IGN] lecture de carte [Termes IGN] légende cartographique [Termes IGN] palette de couleurs [Termes IGN] ressources naturelles [Termes IGN] Roumanie [Termes IGN] taxinomie [Termes IGN] visualisation cartographique Résumé : (auteur) The legends of natural resource taxonomy-based maps (e.g. soil, geological, geomorphological, vegetation, and land cover/land use) need many different distinguishable colors. The existing methods of color selection for map legends are based on the designer subjectivity, ensuring schemes having few colors. An analysis of the modeling and management of colors in digital applications has led to define an algorithm to calculate an objective colorimetric measure of color difference – “DE*ab” – based on the perceptually uniform color model CIELAB. The proposed method consists of a set of specific rules for developing hierarchically structured color schemes and a specific procedure for ensuring selection of a large number of reliably distinguishable colors, based on a color difference threshold. The accuracy of color reproduction in printing processes is also taken into account. The method has been applied to develop a standard of colors for soil maps. It contains 63 colors and has been used for developing a soil map having 41 standard colors. A user test of the method results proved that thresholds of 10 DE*ab units and 15 DE*ab units ensure obtaining acceptably distinguishable colors for displaying/printing maps by using high-quality, respectively, current devices. Three datasets that support the research are given. Numéro de notice : A2021-643 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1942218 Date de publication en ligne : 23/08/2021 En ligne : https://doi.org/10.1080/15230406.2021.1942218 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98340 [article]

A learning-based approach to automatically evaluate the quality of sequential color schemes for maps / Taisheng Chen in Cartography and Geographic Information Science, Vol 48 n° 5 (September 2021)  

Public [article]  inCartography and Geographic Information Science > Vol 48 n° 5 (September 2021) . - pp 377-392 Titre : A learning-based approach to automatically evaluate the quality of sequential color schemes for maps Type de document : Article/Communication Auteurs : Taisheng Chen, Auteur ; Menglin Chen, Auteur ; A - Xing Zhu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 377-392 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] amélioration des couleurs [Termes IGN] apprentissage automatique [Termes IGN] charte de couleurs [Termes IGN] cohérence des couleurs [Termes IGN] contraste de couleurs [Termes IGN] couleur (rédaction cartographique) [Termes IGN] données d'apprentissage [Termes IGN] palette de couleurs [Termes IGN] saturation de la couleur [Termes IGN] visualisation cartographique Résumé : (auteur) Color quality evaluation is key to judging map quality, which can improve data visualization and communication. However, most existing methods for evaluating map colors are tedious and subjective manual methods. In this paper, we study sequential color schemes, a widely used map color type and propose a learning-based approach for evaluating the color quality. The approach consists of two steps. First, we extract and characterize the cartographic factors for determining the quality of sequential color schemes, such as color order, color match, color harmony, color discrimination and color uniformity. Second, we present a model to predict the color quality based on AdaBoost, a type of ensemble learning algorithm with excellent classification performance and use these factors as input data. We conduct a case study based on 781 samples and train the AdaBoost-based model to predict the quality of sequential color schemes. To evaluate the model’s performance, we calculated the area under the receiver operating characteristic (ROC) curve (AUC). The AUC values are 0.983 and 0.977 on the training data and testing data, respectively. These results indicate that the proposed approach can be used to automatically evaluate the quality of sequential color schemes for maps, which helps mapmakers select good colors. Numéro de notice : A2021-642 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1936184 Date de publication en ligne : 29/06/2021 En ligne : https://doi.org/10.1080/15230406.2021.1936184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98335 [article]

Detection of pictorial map objects with convolutional neural networks / Raimund Schnürer in Cartographic journal (the), vol 58 n° 1 (August 2021)  

Public [article]  inCartographic journal (the) > vol 58 n° 1 (August 2021) . - pp 50 - 68 Titre : Detection of pictorial map objects with convolutional neural networks Type de document : Article/Communication Auteurs : Raimund Schnürer, Auteur ; René Sieber, Auteur ; Jost Schmid-Lanter, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 50 - 68 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] base de données d'images [Termes IGN] bibliothèque numérique [Termes IGN] carte ancienne [Termes IGN] carte numérique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] données issues des réseaux sociaux [Termes IGN] objet cartographique [Termes IGN] pictogramme Résumé : (auteur) In this work, realistically drawn objects are identified on digital maps by convolutional neural networks. For the first two experiments, 6200 images were retrieved from Pinterest. While alternating image input options, two binary classifiers based on Xception and InceptionResNetV2 were trained to separate maps and pictorial maps. Results showed that the accuracy is 95–97% to distinguish maps from other images, whereas maps with pictorial objects are correctly classified at rates of 87–92%. For a third experiment, bounding boxes of 3200 sailing ships were annotated in historic maps from different digital libraries. Faster R-CNN and RetinaNet were compared to determine the box coordinates, while adjusting anchor scales and examining configurations for small objects. A resulting average precision of 32% was obtained for Faster R-CNN and of 36% for RetinaNet. Research outcomes are relevant for trawling map images on the Internet and for enhancing the advanced search of digital map catalogues. Numéro de notice : A2021-651 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00087041.2020.1738112 Date de publication en ligne : 11/09/2020 En ligne : https://doi.org/10.1080/00087041.2020.1738112 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98381 [article]

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