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Auteur Gaurav Sinha |
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Validating the use of object-based image analysis to map commonly recognized landform features in the United States / Samantha T. Arundel in Cartography and Geographic Information Science, Vol 46 n° 5 (September 2019)
[article]
Titre : Validating the use of object-based image analysis to map commonly recognized landform features in the United States Type de document : Article/Communication Auteurs : Samantha T. Arundel, Auteur ; Gaurav Sinha, Auteur Année de publication : 2019 Article en page(s) : pp 441 - 455 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] accident géographique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] base de données localisées
[Termes IGN] chaîne de traitement
[Termes IGN] données localisées 3D
[Termes IGN] Etats-Unis
[Termes IGN] relation spatiale
[Termes IGN] relief
[Termes IGN] toponymie localeRésumé : (Auteur) The U.S. Geological Survey (USGS) National Geospatial Program (NGP) seeks to i) create semantically accessible terrain features from the pixel-based 3D Elevation Program (3DEP) data, and ii) enhance the usability of the USGS Geographic Names Information System (GNIS) by associating boundaries with GNIS features whose spatial representation is currently limited to 2D point locations. Geographic object-based image analysis (GEOBIA) was determined to be a promising method to approach both goals. An existing GEOBIA workflow was modified and the resulting segmented objects and terrain categories tested for a strategically chosen physiographic province in the mid-western US, the Ozark Plateaus. The chi-squared test of independence confirmed that there is significant overall spatial association between terrain categories of the GEOBIA and GNIS feature classes. Contingency table analysis also suggests strong category-specific associations between select GNIS and GEOBIA classes. However, 3D visual analysis revealed that GEOBIA objects resembled segmented regions more than they did individual landform objects, with their boundaries often failing to correspond to match what people would likely perceive as landforms. Still, objects derived through GEOBIA can provide initial baseline landscape divisions that can improve the efficiency of more specialized feature extraction methods. Numéro de notice : A2019-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1526652 Date de publication en ligne : 07/11/2018 En ligne : https://doi.org/10.1080/15230406.2018.1526652 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93173
in Cartography and Geographic Information Science > Vol 46 n° 5 (September 2019) . - pp 441 - 455[article]Réservation
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