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Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)
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Titre : Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Boris Jutzi, Auteur ; Clément Mallet , Auteur
Année de publication : 2014 Conférence : PCV 2014, ISPRS Technical Commission 3 Symposium Photogrammetric Computer vision 05/09/2014 07/09/2014 Zurich Suisse OA ISPRS Annals Article en page(s) : pp 181 - 188 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image numérique
[Termes IGN] classification
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de points
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsRésumé : (auteur) 3D scene analysis by automatically assigning 3D points a semantic label has become an issue of major interest in recent years. Whereas the tasks of feature extraction and classification have been in the focus of research, the idea of using only relevant and more distinctive features extracted from optimal 3D neighborhoods has only rarely been addressed in 3D lidar data processing. In this paper, we focus on the interleaved issue of extracting relevant, but not redundant features and increasing their distinctiveness by considering the respective optimal 3D neighborhood of each individual 3D point. We present a new, fully automatic and versatile framework consisting of four successive steps: (i) optimal neighborhood size selection, (ii) feature extraction, (iii) feature selection, and (iv) classification. In a detailed evaluation which involves 5 different neighborhood definitions, 21 features, 6 approaches for feature subset selection and 2 different classifiers, we demonstrate that optimal neighborhoods for individual 3D points significantly improve the results of scene interpretation and that the selection of adequate feature subsets may even further increase the quality of the derived results. Numéro de notice : A2014-799 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-181-2014 Date de publication en ligne : 07/08/2014 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-181-2014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82699
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 (September 2014) . - pp 181 - 188[article]An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data / Wei Zhuang in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)
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Titre : An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data Type de document : Article/Communication Auteurs : Wei Zhuang, Auteur ; Giorgos Mountrakis, Auteur Année de publication : 2014 Article en page(s) : pp 81 – 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] empreinte
[Termes IGN] filtrage numérique d'image
[Termes IGN] forêt
[Termes IGN] forme d'onde
[Termes IGN] groupe
[Termes IGN] identification automatique
[Termes IGN] onde lidar
[Termes IGN] surface du sol
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] traitement de donnéesRésumé : (Auteur) Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA’s major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors. Numéro de notice : A2014-474 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74051
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 81 – 92[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests / Jason R. Parent in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)
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Titre : Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests Type de document : Article/Communication Auteurs : Jason R. Parent, Auteur ; John C. Volin, Auteur Année de publication : 2014 Article en page(s) : pp 134 – 145 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] feuillu
[Termes IGN] forêt
[Termes IGN] objectif grand angulaire
[Termes IGN] photographie aérienne
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Estimates of canopy closure have many important uses in forest management and ecological research. Field measurements, however, are typically not practical to acquire over expansive areas or for large numbers of locations. This problem has been addressed, in recent years, through the use of airborne light detection and ranging (LiDAR) technology which has proven effective in modeling canopy closure remotely. The techniques developed to use LiDAR for this purpose have been designed and evaluated for datasets acquired during leaf-on conditions. However, a large number of LiDAR datasets are acquired during leaf-off conditions since their primary purpose is to generate bare-earth Digital Elevation Models. In this paper, we develop and evaluate techniques for leveraging small-footprint leaf-off LiDAR data to model leaf-on canopy closure in temperate deciduous forests.
We evaluate three techniques for modeling canopy closure: (1) the canopy-to-total-return-ratio (CTRR), (2) the canopy-to-total-pixel-ratio (CTPR), and (3) the hemispherical-viewshed (HV). The first technique has been used widely, in various forms, and has been shown to be effective with leaf-on LiDAR datasets. The CTRR technique that we tested uses the first-return LiDAR data only. The latter two techniques are new contributions that we develop and present in this paper. These techniques use Canopy Height Models (CHM) to detect significant gaps in the forest canopy which are of primary importance in estimating closure.
The techniques we tested each showed good promise for predicting canopy closure using leaf-off LiDAR data with the CTPR and HV models having particularly high correlations with closure estimates from hemispherical photographs. The CTRR model had performance on par with results from previous studies that used leaf-on LiDAR, although, with leaf-off data the model tended to be negatively biased with respect to species having simple and compound leaf types and positively biased for coniferous species. The CTPR and HV models also showed some slight negative biases for compound-leaf species. The biases for the CTPR and HV models were mitigated when the CHM data were smoothed to fill in small gaps. The CHM-based models were robust to changes in the CHM model resolution which suggests that these methods may be applicable to a variety of small-footprint LiDAR datasets. In this research, the new CTPR and HV methods showed a strong ability to predict canopy closure using leaf-off data, however, future work will be needed to test the applicability of the models to variations in LiDAR datasets, forest types, and topography.Numéro de notice : A2014-477 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74054
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 134 – 145[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Automated registration of dense terrestrial laser-scanning point clouds using curves / B. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)
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Titre : Automated registration of dense terrestrial laser-scanning point clouds using curves Type de document : Article/Communication Auteurs : B. Yang, Auteur ; Yufu Zang, Auteur Année de publication : 2014 Article en page(s) : pp 109 – 121 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement de formes
[Termes IGN] ligne caractéristique
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) This paper proposes an automatic method for registering terrestrial laser scans in terms of robustness and accuracy. The proposed method uses spatial curves as matching primitives to overcome the limitations of registration methods based on points, lines, or patches as primitives. These methods often have difficulty finding correspondences between the scanned point clouds of freeform surfaces (e.g., statues, cultural heritage). The proposed method first clusters visually prominent points selected according to their associated geometric curvatures to extract crest lines which describe the shape characteristics of point clouds. Second, a deformation energy model is proposed to measure the shape similarity of these crest lines to select the correct matching-curve pairs. Based on these pairs, good initial orientation parameters can be obtained, resulting in fine registration. Experiments were undertaken to evaluate the robustness and accuracy of the proposed method, demonstrating a reliable and stable solution for accurately registering complex scenes without good initial alignment. Numéro de notice : A2014-475 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.05.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.05.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74052
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 109 – 121[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves / Rubén Valbuena in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)
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Titre : Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves Type de document : Article/Communication Auteurs : Rubén Valbuena, Auteur ; Jari Vauhkonen, Auteur ; Petteri Packalen, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 23 – 33 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] arbre (flore)
[Termes IGN] courbe de Lorenz
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] indicateur
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scanning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indicators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient (GC), Lorenz asymmetry (LA), the proportions of basal area (BALM) and stem density (NSLM) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list estimation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN imputation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in forested areas. Numéro de notice : A2014-473 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74050
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 23 – 33[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Cross-correlation of diameter measures for the co-registration of forest inventory plots with airborne laser scanning data / Jean-Matthieu Monnet in Forests, vol 5 n° 9 (September 2014)
PermalinkError analysis of a mobile terrestrial LiDAR system / M. Leslar in Geomatica, vol 68 n° 3 (September 2014)
PermalinkA structure-aware global optimization method for reconstructing 3-D tree models from terrestrial laser scanning data / Z. Wang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 2 (September 2014)
PermalinkEstimation of the timber quality of scots pine with terrestrial laser scanning / Ville Kankare in Forests, vol 5 n° 8 (August 2014)
PermalinkMise en service d'un système de scanning mobile de la maison IGI GmbH : gestion du segment de contrôle géométrique / A. Perrissol in Géomatique suisse, vol 112 n° 8 (août 2014)
PermalinkCalibration of area based diameter distribution with individual tree based diameter estimates using airborne laser scanning / Qing Xu in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
PermalinkDetection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning / Andrès Serna in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
PermalinkGround and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces / Domen Mongus in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
PermalinkL'intégration du scanner 3D dans la technologie BIM / Maxime Romain De La Touche in Géomatique expert, n° 99 (01/07/2014)
PermalinkRecalage rigide de relevés laser par mise en correspondance robuste basée sur des segments / Martyna Poreba in Revue Française de Photogrammétrie et de Télédétection, n° 207 (Juillet 2014)
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