Centre de documentation
scientifique

DART-Lux: An unbiased and rapid Monte Carlo radiative transfer method for simulating remote sensing images / Yingjie Wang in Remote sensing of environment, vol 274 (June 2022)  

Public [article]  inRemote sensing of environment > vol 274 (June 2022) . - n° 112973 Titre : DART-Lux: An unbiased and rapid Monte Carlo radiative transfer method for simulating remote sensing images Type de document : Article/Communication Auteurs : Yingjie Wang, Auteur ; Abdelaziz Kallel, Auteur ; Xuebo Yang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112973 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] bande spectrale [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] image à haute résolution [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle de transfert radiatif [Termes IGN] radiance [Termes IGN] réflectance directionnelle [Termes IGN] scène forestière [Termes IGN] scène urbaine Résumé : (auteur) Accurate and efficient simulation of remote sensing images is increasingly needed in order to better exploit remote sensing observations and to better design remote sensing missions. DART (Discrete Anisotropic Radiative Transfer), developed since 1992 based on the discrete ordinates method (i.e., standard mode DART-FT), is one of the most accurate and comprehensive 3D radiative transfer models to simulate the radiative budget and remote sensing observations of urban and natural landscapes. Recently, a new method, called DART-Lux, was integrated into DART model to address the requirements of massive remote sensing data simulation for large-scale and complex landscapes. It is developed based on efficient Monte Carlo light transport algorithms (i.e., bidirectional path tracing) and on DART model framework. DART-Lux can accurately and rapidly simulate the bidirectional reflectance factor (BRF) and spectral images of arbitrary landscapes. This paper presents its theory, implementation, and evaluation. Its accuracy, efficiency and advantages are also discussed. The comparison with standard DART-FT in a variety of scenarios shows that DART-Lux is consistent with DART-FT (relative differences Numéro de notice : A2022-398 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.112973 Date de publication en ligne : 26/03/2022 En ligne : https://doi.org/10.1016/j.rse.2022.112973 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100698 [article]

Target-based automated matching of multiple terrestrial laser scans for complex forest scenes / Xuming Ge in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 179 (September 2021) . - pp 1 - 13 Titre : Target-based automated matching of multiple terrestrial laser scans for complex forest scenes Type de document : Article/Communication Auteurs : Xuming Ge, Auteur ; Qing Zhu, Auteur Année de publication : 2021 Article en page(s) : pp 1 - 13 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] appariement de données localisées [Termes IGN] biomasse aérienne [Termes IGN] biomasse forestière [Termes IGN] densité de la végétation [Termes IGN] détection d'arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] scène forestière [Termes IGN] semis de points Résumé : (Auteur) Terrestrial laser scanners are widely used to derive unbiased and non-destructive estimates of the vertical distribution of the plant area index and plant area volume density at plot-level scales, as well as the above-ground biomass, height, and diameter at breast height of individual trees. Multiple scans are often employed to capture and register data so that all of the stems can be detected and their complete forms can be analyzed. Researchers have traditionally preferred target-less strategies to register scans because of their low cost and convenience. However, in complex forest scenes, even state-of-the-art approaches cannot guarantee the success of any pairwise registration. In this study, we present an automated target-based processing approach for the registration of unordered scans in complex forest scenes. In contrast to previous studies, the proposed registration method automatically detects the artificial targets and builds a geometric network to judge their connectivity. A pose graph is then exploited to combine these data with the corresponding pairwise transformation, and then the scans are integrated into a unified coordinate system. This method is more robust and efficient than target-less approaches because it is independent of the characteristics of individual trees and does not require ground information. In an experimental scenario, we use an extremely complex wild bamboo forest scene to evaluate the performance of the proposed approach in terms of robustness, accuracy, and efficiency. Numéro de notice : A2021-573 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.06.019 Date de publication en ligne : 15/07/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.06.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98173 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2021091	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2021093	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2021092	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Weighted spherical sampling of point clouds for forested scenes / Alex Fafard in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 10 (October 2020) . - pp 619 - 625 Titre : Weighted spherical sampling of point clouds for forested scenes Type de document : Article/Communication Auteurs : Alex Fafard, Auteur ; Ali Rouzbeh Kargar, Auteur ; Jan Van Aardt, Auteur Année de publication : 2020 Article en page(s) : pp 619 - 625 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] coordonnées sphériques [Termes IGN] densité de la végétation [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] échantillonnage [Termes IGN] mangrove [Termes IGN] Micronésie [Termes IGN] scène forestière [Termes IGN] semis de points [Termes IGN] volume en bois Résumé : (Auteur) Terrestrial laser scanning systems are characterized by a sampling pattern which varies in point density across the hemisphere. Additionally, close objects are over-sampled relative to objects that are farther away. These two effects compound to potentially bias the three-dimensional statistics of measured scenes. Previous methods of sampling have resulted in a loss of structural coherence. In this article, a method of sampling is proposed to optimally sample points while preserving the structure of a scene. Points are sampled along a spherical coordinate system, with probabilities modulated by elevation angle and squared distance from the origin. The proposed approach is validated through visual comparison and stem-volume assessment in a challenging mangrove forest in Micronesia. Compared to several well-known sampling techniques, the proposed approach reduces sampling bias and shows strong performance in stem-reconstruction measurement. The proposed sampling method matched or exceeded the stem-volume measurement accuracy across a variety of tested decimation levels. On average it achieved 3.0% higher accuracy at estimating stem volume than the closest competitor. This approach shows promise for improving the evaluation of terrestrial laser-scanning data in complex scenes. Numéro de notice : A2020-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.10.619 Date de publication en ligne : 01/10/2020 En ligne : https://doi.org/10.14358/PERS.86.10.619 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96093 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2020101	SL	Revue	Centre de documentation	Revues en salle	Disponible