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Structural damage assessments from Ikonos data using change detection, object-oriented segmentation, and classification techniques / D.H.A. Khudhairy in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 7 (July 2005) . - pp 825 - 835 Titre : Structural damage assessments from Ikonos data using change detection, object-oriented segmentation, and classification techniques Type de document : Article/Communication Auteurs : D.H.A. Khudhairy, Auteur ; I. Caravaggi, Auteur ; S. Giada, Auteur Année de publication : 2005 Article en page(s) : pp 825 - 835 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse en composantes principales [Termes IGN] Brest [Termes IGN] détection de changement [Termes IGN] dommage matériel [Termes IGN] eCognition [Termes IGN] extraction automatique [Termes IGN] image à résolution métrique [Termes IGN] image Ikonos [Termes IGN] milieu urbain [Termes IGN] morphologie mathématique [Termes IGN] Palestine [Termes IGN] segmentation d'image Résumé : (Auteur) Recent improvements in the spatial resolution of commercial satellite imagery make it possible to apply very high-resolution (VHR) satellite data for assessing structural damage in the aftermath of humanitarian crises, such as, armed conflicts. Visual interpretation of pre- and post-crisis very high-resolution satellite imagery is the most straightforward method for discriminating structural damage and assessing its extent. However, the feasibility of using visual interpretation alone diminishes in the cases of large and dense urban settlements and spatial resolutions in the range of 2 m to 3 meters and larger. Visual interpretation can be further complicated at spatial resolutions greater than 1 m if accompanied by shadow formation and differences in sensor and solar conditions between the pre- and post-conflict images. In this study, we address these problems through investigating the use of traditional change techniques, namely, image differencing and principle component analysis, with an object-oriented image classification software, e-Cognition. Pre-conflict Ikonos (2 m resolution) images of Jenin in the Palestinian territories and Brest (1 m resolution) in FYROM were classified using the e-Cognition software. Thereafter, the pre-conflict classification was used to guide the classification, using e-Cognition, of the pixel-based change detection analysis. The second part of the study examines the feasibility of using mathematical morphological operators to automatically identify likely structurally damaged zones in dense urban settings. The overall results are promising and show that object-oriented segmentation and classification systems facilitate the interpretation of change detection results derived from very high-resolution (1 m and 2 m) commercial satellite data. The results show that object-oriented classification techniques enhance quantitative analysis of traditional pixel-based change detection applied to very high-resolution satellite data and facilitate the interpretation of changes in urban features. Finally, the results suggest that mathematical morphological methods are a potential new avenue for automatically extracting likely damaged zones from very high-resolution satellite imagery in the aftermath of disasters. Numéro de notice : A2005-298 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.7.825 En ligne : https://doi.org/10.14358/PERS.71.7.825 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27434 [article]

DEM generation and building detection from Lidar data / R. Ma in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 7 (July 2005) . - pp 847 - 854 Titre : DEM generation and building detection from Lidar data Type de document : Article/Communication Auteurs : R. Ma, Auteur Année de publication : 2005 Article en page(s) : pp 847 - 854 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] contour [Termes IGN] densité des points [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] données localisées [Termes IGN] modèle numérique de surface [Termes IGN] point d'appui [Termes IGN] reconstruction 3D Résumé : (Auteur) Object reconstruction has attracted great attention from both computer vision and photogrammetry communities, and new technologies are being introduced into this research society. Lidar (Light Detection And Ranging) has become well recognized in the geomatics community since the late 1990s. Compared with traditional photogrammetry, lidar has advantages in measuring surface in terms of accuracy and density, automation, and fast delivery time. There is a large market in geo-data acquisition and object recognition for lidar technology (Baltsavias, 1999). In a general sense, lidar is a companion technology for traditional photogrammetry. The direct product that can be derived from lidar data is the DSM (Digital Surface Model), which depicts the topography of the earth's surface, including objects above the terrain. Further processing can be carried out to generate DEM (Digital Terrain Model) and object models like buildings, which is very useful information in telecommunication, city planning, flood control, and tourism. Morphology and classification are two commonly used methods in DEM generation and object reconstruction. However, these two methods are either sensitive to errors or of low accuracy. In this paper, a new method is proposed to extract ground points for DEM generation and to detect points belonging to buildings. A new method for boundary regularization is also proposed. The results show that buildings can be detected with high accuracy from lidar data. Numéro de notice : A2005-299 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.7.847 En ligne : https://doi.org/10.14358/PERS.71.7.847 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27435 [article]

A split-and-merge technique for automated reconstruction of roof planes / Kourosh Khoshelham in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 7 (July 2005) . - pp 855 - 862 Titre : A split-and-merge technique for automated reconstruction of roof planes Type de document : Article/Communication Auteurs : Kourosh Khoshelham, Auteur ; Z. Li, Auteur ; B. King, Auteur Année de publication : 2005 Article en page(s) : pp 855 - 862 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] extraction du sursol [Termes IGN] hauteur du bâti [Termes IGN] modèle numérique de surface [Termes IGN] morphologie urbaine [Termes IGN] partition de surface [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation d'image Résumé : (Auteur) Automated reconstruction of buildings from different data sources has been one of the most challenging problems in photogrammetry and computer vision. Systems for automated building reconstruction fail in many cases due to complexities involved in the data including image noise, occlusion, shadow, and low contrast, as well as, low accuracy or density of height data. In this paper, the problem of overgrown and undergrown regions in the segmentation of aerial images is discussed, and a split-and-merge technique is presented to overcome this problem by making use of height data. This technique is based on splitting image regions whose associated height points do not fall in a single plane, and merging coplanar neighboring regions. A robust plane-fitting method is used to fit planar surfaces to height points that are highly contaminated by gross errors. Final roof planes are extracted out of the image planar regions by checking their slope and height over a morphologically opened Dsm. An experimental evaluation is conducted, and its results indicate the capability of the proposed technique in splitting overgrown regions, merging undergrown coplanar regions, and selecting the final roof planes. Also, the method is shown to be computationally efficient, and the reconstructed roof planes are of acceptable accuracy. Numéro de notice : A2005-300 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.7.855 En ligne : https://doi.org/10.14358/PERS.71.7.855 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27436 [article]