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An efficient visualization method for polygonal data with dynamic simplification / Mingguang Wu in ISPRS International journal of geo-information, vol 7 n° 4 (April 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 4 (April 2018) Titre : An efficient visualization method for polygonal data with dynamic simplification Type de document : Article/Communication Auteurs : Mingguang Wu, Auteur ; Taisheng Chen, Auteur ; Kun Zhang, Auteur ; Zhimin Jing, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de Douglas-Peucker [Termes IGN] données localisées [Termes IGN] intégrité topologique [Termes IGN] maillage [Termes IGN] OpenStreetMap [Termes IGN] polygone [Termes IGN] polyligne [Termes IGN] simplification de contour [Termes IGN] tessellation [Termes IGN] visualisation de données [Vedettes matières IGN] Généralisation Résumé : (Auteur) Polygonal data often require rendering with symbolization and simplification in geovisualization. A common issue in existing methods is that simplification, symbolization and rendering are addressed separately, causing computational and data redundancies that reduce efficiency, especially when handling large complex polygonal data. Here, we present an efficient polygonal data visualization method by organizing the simplification, tessellation and rendering operations into a single mesh generalization process. First, based on the sweep line method, we propose a topology embedded trapezoidal mesh data structure to organize the tessellated polygons. Second, we introduce horizontal and vertical generalization operations to simplify the trapezoidal meshes. Finally, we define a heuristic testing algorithm to efficiently preserve the topological consistency. The method is tested using three OpenStreetMap datasets and compared with the Douglas Peucker algorithm and the Binary Line Generalization tree-based method. The results show that the proposed method improves the rendering efficiency by a factor of six. Efficiency-sensitive mapping applications such as emergency mapping could benefit from this method, which would significantly improve their visualization performances. Numéro de notice : A2018-108 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7040138 En ligne : https://doi.org/10.3390/ijgi7040138 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89537 [article]

Mapping forest characteristics at fine resolution across large landscapes of the southeastern united states using NAIP imagery and FIA field plot data / John Hogland in ISPRS International journal of geo-information, vol 7 n° 4 (April 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 4 (April 2018) Titre : Mapping forest characteristics at fine resolution across large landscapes of the southeastern united states using NAIP imagery and FIA field plot data Type de document : Article/Communication Auteurs : John Hogland, Auteur ; Nathaniel Anderson, Auteur ; Joseph St. Peter, Auteur ; Jason Drake, Auteur ; Paul Medley, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] composition floristique [Termes IGN] densité du bois [Termes IGN] Etats-Unis [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Pinus (genre) [Termes IGN] surface terrière [Termes IGN] télédétection aérienne [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Accurate information is important for effective management of natural resources. In the field of forestry, field measurements of forest characteristics such as species composition, basal area, and stand density are used to inform and evaluate management activities. Quantifying these metrics accurately across large landscapes in a meaningful way is extremely important to facilitate informed decision-making. In this study, we present a remote sensing based methodology to estimate species composition, basal area and stand tree density for pine and hardwood tree species at the spatial resolution of a Forest Inventory Analysis (FIA) program plot (78 m by 70 m). Our methodology uses textural metrics derived at this spatial scale to relate plot summaries of forest characteristics to remotely sensed National Agricultural Imagery Program (NAIP) aerial imagery across broad extents. Our findings quantify strong relationships between NAIP imagery and FIA field data. On average, models of basal area and trees per acre accounted for 43% of the variation in the FIA data, while models identifying species composition had less than 15.2% error in predicted class probabilities. Moreover, these relationships can be used to spatially characterize the condition of forests at fine spatial resolutions across broad extents. Numéro de notice : A2018-109 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7040140 En ligne : https://doi.org/10.3390/ijgi7040140 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89538 [article]