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3D building model reconstruction from multi-view aerial imagery and Lidar data / Liang Cheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 2 (February 2011)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 2 (February 2011) . - pp 125 - 139 Titre : 3D building model reconstruction from multi-view aerial imagery and Lidar data Type de document : Article/Communication Auteurs : Liang Cheng, Auteur ; J. Gong, Auteur ; M. Li, Auteur ; Y. Liu, Auteur Année de publication : 2011 Article en page(s) : pp 125 - 139 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] contour [Termes IGN] données lidar [Termes IGN] données multisources [Termes IGN] image aérienne [Termes IGN] intégration de données [Termes IGN] précision géométrique (imagerie) [Termes IGN] reconstruction 3D du bâti Résumé : (Auteur) A novel approach by integrating multi-view aerial imagery and lidar data is proposed to reconstruct 3D building models with accurate geometric position and fine details. First, a new algorithm is introduced for determination of principal orientations of a building, thus benefiting to improve the correctness and robustness of boundary segment extraction in aerial imagery. A new dynamic selection strategy based on lidar point density analysis and K-means clustering is then proposed to identify boundary segments from non-boundary segments. Second, 3D boundary segments are determined by incorporating lidar data and the 2D segments extracted from multi-view imagery. Finally, a new strategy for 3D building model reconstruction including automatic recovery of lost boundaries and robust reconstruction of rooftop patches is introduced. The experimental results indicate that the proposed approach can provide high quality 3D models with high-correctness, high-completeness, and good geometric accuracy. Numéro de notice : A2011-045 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.77.2.125 En ligne : https://doi.org/10.14358/PERS.77.2.125 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30826 [article]

Sub-canopy soil moisture modeling in n-dimensional spectral feature space / A. Ghulam in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 2 (February 2011)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 2 (February 2011) . - pp 149 - 156 Titre : Sub-canopy soil moisture modeling in n-dimensional spectral feature space Type de document : Article/Communication Auteurs : A. Ghulam, Auteur ; T. Kusky, Auteur ; T. Teyip, Auteur ; Q. Qin, Auteur Année de publication : 2011 Article en page(s) : pp 149 - 156 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] humidité du sol [Termes IGN] image aérienne [Termes IGN] image Terra-MODIS [Termes IGN] modélisation [Termes IGN] signature spectrale [Termes IGN] sous-bois Résumé : (Auteur) This paper attempts to quantify soil moisture in various canopy cover conditions using n-dimensional spectral signatures, including land surface temperature, vegetation index, albedo, and others. First, the feature vector between the pixels and various moisture contents was indentified. Normalization of the varying distance from a user-defined initial state to any pixel location, and coefficients related with n-dimensional spectral feature space were calculated, assigning weights to each parameter. Then, a soil moisture index was developed using a linear combination of the first order polynomials. The Extended Fourier Amplitude Sensitivity Test (eFAST) was used to calculate the relative variance contribution of model input parameters to the variance of soil moisture predictions. Results derived from satellite data including Enhanced Thematic Mapper Plus (ETM+) and the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery demonstrated significant correlations between the index and soil moisture obtained for different ecosystems and vegetation cover. The best agreement, the coefficient of determination (R2), between the index and soil moisture were 0.58 and 0.65 for ETM+ and MODIS data, respectively. eFAST sensitivity analysis indicates that land surface temperature might be the most determinant factor in soil moisture estimation, then albedo, followed by NDVI. Numéro de notice : A2011-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.77.2.149 En ligne : https://doi.org/10.14358/PERS.77.2.149 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30827 [article]

A genetic algorithm approach to moving threshold optimization for binary change detection / J. Im in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 2 (February 2011)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 77 n° 2 (February 2011) . - pp 167 - 180 Titre : A genetic algorithm approach to moving threshold optimization for binary change detection Type de document : Article/Communication Auteurs : J. Im, Auteur ; Zhong Lu, Auteur ; J. Jensen, Auteur Année de publication : 2011 Article en page(s) : pp 167 - 180 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme génétique [Termes IGN] détection de changement [Termes IGN] image Quickbird [Termes IGN] seuillage d'image Résumé : (Auteur) This study investigated the use of a genetic algorithm (GA) approach, a widely used optimization method, to identify optimum thresholds for remote sensing-based binary change detection. Automated GA-based calibration models using a moving threshold window (MTW) were developed and tested using a case study. Two sets of the bi-temporal QuickBird imagery were used to evaluate the new optimization models. The GA-based models using MTW were free from the assumption of symmetry of thresholds for difference- or ratio-type of change-enhanced images, unlike traditional binary change detection methods, allowing more flexibility and efficiency in selecting optimum thresholds. Exhaustive search techniques using symmetric threshold window (STW) and MTW were evaluated for comparison. The stability of the GA-based models in terms of accuracy variation was also examined. The GA-based calibration models successfully identified optimum thresholds without a significant decrease in accuracy. The GA-based models using MTW outperformed the GA-based model using STW in both calibration and validation, revealing that optimum thresholds tended to be asymmetric. Multiple change-enhanced images generally resulted in better performance than single change-enhanced images based on the GA-based models. Numéro de notice : A2011-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.77.2.167 En ligne : https://doi.org/10.14358/PERS.77.2.167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30828 [article]