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Using aerial imagery and GIS in automated building footprint extraction and shape recognition for earthquake risk assessment of urban inventories / L. Sahar in IEEE Transactions on geoscience and remote sensing, vol 48 n° 9 (September 2010)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 48 n° 9 (September 2010) . - pp 3511 - 3520 Titre : Using aerial imagery and GIS in automated building footprint extraction and shape recognition for earthquake risk assessment of urban inventories Type de document : Article/Communication Auteurs : L. Sahar, Auteur ; S. Muthukumar, Auteur ; S. French, Auteur Année de publication : 2010 Article en page(s) : pp 3511 - 3520 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] extraction automatique [Termes IGN] image aérienne [Termes IGN] reconnaissance de formes [Termes IGN] reconstruction 2D du bâti [Termes IGN] risque naturel [Termes IGN] séisme [Termes IGN] système d'information géographique [Termes IGN] traitement automatique de données Résumé : (Auteur) Earthquakes cause massive loss of property and lives, and mitigating their potential effects requires accurate modeling and simulation of their impacts. Earthquake building damage modeling and risk assessment applications require accurate accounts of inventories at risk and their attributes such as structure type, usage, size, number of stories, shape, year built, value, etc. This paper describes the development of algorithms for automatically extracting and recognizing 2-D building shape information using integrated aerial imagery processing and Geographic Information Systems data. We use vector parcel geometries and their attributes to simplify the building extraction task by limiting the processing geography. Extraction is significantly improved by innovatively weighting the histograms. Extracted buildings are cleaned, simplified, and run through 2-D shape recognition routines that classify the footprint. We discuss reasons for successes and failures in both extraction and recognition. Numéro de notice : A2010-572 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2047260 En ligne : https://doi.org/10.1109/TGRS.2010.2047260 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30763 [article]

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