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Building extraction from Lidar data using statistical methods / Haval Abdul-Jabbar Sadeq in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 1 (January 2021) . - pp 33 - 42 Titre : Building extraction from Lidar data using statistical methods Type de document : Article/Communication Auteurs : Haval Abdul-Jabbar Sadeq, Auteur Année de publication : 2021 Article en page(s) : pp 33 - 42 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de données [Termes IGN] classification orientée objet [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction de traits caractéristiques [Termes IGN] Ransac (algorithme) [Termes IGN] segmentation sémantique [Termes IGN] semis de points Résumé : (Auteur) In this article, a straightforward, intuitive method for lidar data classification and building extraction, based on statistical analysis, is presented. The classification of the point cloud into ground and nonground is begun by individually testing each point within the point cloud using the statistical mean height. In this operation, various window sizes are specified, and the mean is obtained at each size. The points that are above the mean are saved and divided by the number of windows to obtain the proportion. Points are considered non-ground if their proportion is higher than the assigned threshold, and otherwise ground. An algorithm for classifying the obtained nonground point cloud into buildings and trees is also illustrated in this article. First the nonground points are labeled, then each label is tested individually. The process begins with segmenting each label. Then comes testing of whether each segment of points can be fitted within a specific plane. The label of the point cloud is considered a building if the number of segments considered as planes is larger than those considered as nonplanes; otherwise it is classified as a tree. Numéro de notice : A2021-055 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.1.33 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.14358/PERS.87.1.33 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96760 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021011	SL	Revue	Centre de documentation	Revues en salle	Disponible

Georeferencing with self-calibration for airborne full-waveform Lidar data using digital elevation model / Qinghua Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 1 (January 2021) . - pp 43 - 52 Titre : Georeferencing with self-calibration for airborne full-waveform Lidar data using digital elevation model Type de document : Article/Communication Auteurs : Qinghua Li, Auteur ; Jie Shan, Auteur Année de publication : 2021 Article en page(s) : pp 43 - 52 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] auto-étalonnage [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] forme d'onde pleine [Termes IGN] géoréférencement [Termes IGN] modèle géométrique de prise de vue [Termes IGN] modèle numérique de surface [Termes IGN] optimisation (mathématiques) [Termes IGN] point d'appui [Termes IGN] synchronisation Résumé : (Auteur) Precise georeferencing of airborne full-waveform lidar is a complex process. On one hand, no ground control points are visible due to heavy canopy. While on the other hand, precise georeferencing relies on ground control. As an alternative, we propose to use an available digital elevation model (DEM ) as control. The mathematical framework minimizes the difference between the lidar DEM and the reference DEM. Our solution consists of two steps: initial optimization to find reliable ground points through iterative filtering and georeferencing, and fine optimization to achieve precise georeferencing and lidar system calibration. Through this approach, the wave-form-derived DEM can best fit the reference DEM, with a mean of 0.937 m and standard deviation of 0.792 m, while the time-synchronization offset and boresight angles are simultaneously determined, i.e., self-calibrated. This development provides a novel georeferencing approach with self-calibration for lidar data without using conventional ground control points. Numéro de notice : A2021-056 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.1.43 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.14358/PERS.87.1.43 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96766 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021011	SL	Revue	Centre de documentation	Revues en salle	Disponible

An improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images / Behrooz Moradi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 1 (January 2021) . - pp 53 - 69 Titre : An improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images Type de document : Article/Communication Auteurs : Behrooz Moradi, Auteur ; Mohammad Javad Valadan Zoej, Auteur ; Sayad Yaghoobi, Auteur ; Somayeh Yavari, Auteur Année de publication : 2021 Article en page(s) : pp 53 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] géoréférencement [Termes IGN] image à haute résolution [Termes IGN] image Geoeye [Termes IGN] image Ikonos [Termes IGN] Iran [Termes IGN] modèle géométrique de prise de vue [Termes IGN] modèle par fonctions rationnelles [Termes IGN] modélisation 3D Résumé : (Auteur) Recently, linear features in remotely sensed imagery have gained much attention because of their unique characteristics compared to other control features. For georeferencing high-resolution satellite images, the observations in the mathematical equations (slope and y-intercept) of the corresponding control lines in the two spaces are considered the same based on recent studies. However, the use of such assumptions causes error and reduces the accuracy of registration. The aim of this article is to present a methodology based on a quasi-observation assumption in the mathematical equations in the process of georeferencing. Experimental results for IKONOS and GeoEye images over two different cities of Iran indicate that the quasi-observation assumption can increase the average registration accuracy up to 48.96% and 24.77% using 3D-affine and rational function models, respectively. This improvement in accuracy increases the processing time by 31.48% over traditional approaches; however, the proposed methodology can be regarded as an efficient solution. Numéro de notice : A2021-057 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.1.53 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.14358/PERS.87.1.53 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96768 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021011	SL	Revue	Centre de documentation	Revues en salle	Disponible