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Automated fusion of forest airborne and terrestrial point clouds through canopy density analysis / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 94 - 107 Titre : Automated fusion of forest airborne and terrestrial point clouds through canopy density analysis Type de document : Article/Communication Auteurs : Wenxia Dai, Auteur ; Bisheng Yang, Auteur ; Xinlian Liang, Auteur ; Zhen Dong, Auteur ; Ronggang Huang, Auteur ; Yunsheng Wang, Auteur ; Wuyan Li, Auteur Année de publication : 2019 Article en page(s) : pp 94 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] algorithme ICP [Termes descripteurs IGN] canopée [Termes descripteurs IGN] données TLS (télémétrie) [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] fusion de données multisource [Termes descripteurs IGN] image ADAR [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surveillance forestière Résumé : (Auteur) Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) systems are effective ways to capture the 3D information of forests from complementary perspectives. Registration of the two sources of point clouds is necessary for various forestry applications. Since the forest point clouds show irregular and natural point distributions, standard registration methods working on geometric keypoints (e.g., points, lines, and planes) are likely to fail. Hence, we propose a novel method to register the ALS and TLS forest point clouds through density analysis of the crowns. The proposed method extracts mode-based keypoints by the mean shift method and aligns them by maximum likelihood estimation. Firstly, the differences in the point densities of the ALS and TLS crowns are minimized to produce analogous modes, which represent the local maxima of the underlying probability density function (PDF). The mode-based keypoints are then aligned through the coherent point drift (CPD) algorithm, which is independent of the descriptor similarities and considers the alignment as a maximum likelihood estimation problem. The sets of keypoints derived from the two data sources need not be equal. Finally, the recovered transformation is applied to the original point clouds and refined through the standard iterative closest point (ICP) algorithm. In contrast to some of the existing methods, the proposed method avoids the geometric description of the forest point clouds. Furthermore, additional information such as tree diameter or height is not required to evaluate the similarities. The experiments in this study were conducted in a Scandinavian boreal forest, located in Evo, Finland. The proposed method was tested on four datasets (ALS data: a circle with a diameter of 60 m, multi-scan TLS data: 32 × 32 m) with heterogeneous tree species and structures. The results showed that the proposed probabilistic-based method obtains a good performance with a 3D distance residual of 0.069 m, and improved the accuracy of the registration when compared with the existing methods. Numéro de notice : A2019-318 Thématique : FORET/IMAGERIE Nature : Article DOI : doi.org/10.1016/j.isprsjprs.2019.08.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.008 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93356 [article]

Addressing overfitting on point cloud classification using Atrous XCRF / Hasan Asy’ari Arief in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 155 (September 2019) . - pp 90 - 101 Titre : Addressing overfitting on point cloud classification using Atrous XCRF Type de document : Article/Communication Auteurs : Hasan Asy’ari Arief, Auteur ; Ulf Geir Indahl, Auteur ; Geir-Harald Strand, Auteur ; Håvard Tveite, Auteur Année de publication : 2019 Article en page(s) : pp 90 - 101 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] champ aléatoire conditionnel [Termes descripteurs IGN] classification automatique [Termes descripteurs IGN] réseau de neurones profond [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] semis de points Résumé : (Auteur) Advances in techniques for automated classification of point cloud data introduce great opportunities for many new and existing applications. However, with a limited number of labelled points, automated classification by a machine learning model is prone to overfitting and poor generalization. The present paper addresses this problem by inducing controlled noise (on a trained model) generated by invoking conditional random field similarity penalties using nearby features. The method is called Atrous XCRF and works by forcing a trained model to respect the similarity penalties provided by unlabeled data. In a benchmark study carried out using the ISPRS 3D labeling dataset, our technique achieves 85.0% in term of overall accuracy, and 71.1% in term of F1 score. The result is on par with the current best model for the benchmark dataset and has the highest value in term of F1 score. Additionally, transfer learning using the Bergen 2018 dataset, without model retraining, was also performed. Even though our proposal provides a consistent 3% improvement in term of accuracy, more work still needs to be done to alleviate the generalization problem on the domain adaptation and the transfer learning field. Numéro de notice : A2019-312 Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.07.002 date de publication en ligne : 11/07/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.07.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93337 [article]

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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation / Wioleta Błaszczak-Bąk in Survey review, vol 51 n° 368 (September 2019)  

Public [article]  inSurvey review > vol 51 n° 368 (September 2019) . - pp 422 - 430 Titre : Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation Type de document : Article/Communication Auteurs : Wioleta Błaszczak-Bąk, Auteur ; Marian Poniewiera, Auteur ; Anna Sobieraj-Żłobińska, Auteur ; Michal Kowalik, Auteur Année de publication : 2019 Article en page(s) : pp 422 - 430 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] généralisation de MNT [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] réduction Mots-clés libres : Optimum Dataset method Résumé : (Auteur) Modern data-acquisition technologies provide large datasets. Such datasets are often cumbersome for rational processing, and their processing is time consuming. Therefore, there are several methods that can enable the reduction of the dataset size. One of them is generalisation of the Digital Terrain Model (DTM) or the reduction method within the initial processing of measurement data. Another method can be the Optimum Dataset (OptD) method. This paper presents two approaches towards decreasing the Light Detection and Ranging dataset. The first approach is based on the process of DTM generalisation, the second one is based on the application of the OptD method. The reduced datasets were used for isoline map creation depicting the overflow land in open-pit mining. It was proved that the reduction needs to be planned deliberately and that the degree of reduction should be performed in a way that allows to maintain the characteristics of the terrain. Numéro de notice : A2019-368 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 1080/00396265.2018.1474685 date de publication en ligne : 26/06/2018 En ligne : https://doi.org/10.1080/00396265.2018.1474685 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93474 [article]

Automatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 41 - 58 Titre : Automatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery Type de document : Article/Communication Auteurs : Zille Hussnain, Auteur ; Sander J. Oude Elberink, Auteur ; George Vosselman, Auteur ; George Vosselman, Auteur Année de publication : 2019 Article en page(s) : pp 41 - 58 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] appariement de points [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] extraction de points [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] point de liaison (imagerie) [Termes descripteurs IGN] Rotterdam [Termes descripteurs IGN] télémètre laser terrestre [Termes descripteurs IGN] télémétrie laser mobile Résumé : (Auteur) Poor GNSS measurements in urban areas caused by blocked GNSS signals and multi-path is a well-known problem, which leads to an inaccurate trajectory estimation of Mobile Laser Scanning (MLS) platforms. Consequently, the MLS point cloud contains positioning errors. This paper presents a new method for the automatic extraction of accurate 3D tie points for the trajectory adjustment of MLS platforms in GNSS denied or troubled areas. The new method relies on aerial imagery as a reliable external source of reference provided that accurate exterior orientation parameters are available. Accordingly, one of the main objectives is to register the mobile laser scanning point cloud with corresponding aerial images. The matches between aerial images are used to obtain 3D tie points by forward intersection. By also determining the corresponding locations in the point cloud we obtain a 3D-3D correspondence between the MLS point cloud and the aerial images. In the future, the obtained 3D-3D correspondences will be used for trajectory adjustment. Our automatic tie point extraction procedure is tested on two independent MLS point clouds. The point clouds were acquired by two different platforms in Rotterdam. The aerial imagery of the same area was acquired at a different time. We evaluated the matching results for both datasets and concluded that the new procedure reliably extracted the 3D tie points for 55% of the tiles of the size of 90 m from the first MLS dataset. In the second dataset, 60% of the tiles of size 74 m yielded reliable 3D tie points. It is not necessary to successfully register all tiles because the results of this work will be used for the trajectory adjustment and the IMU can reliably support the positioning for small intervals. Numéro de notice : A2019-263 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.010 date de publication en ligne : 04/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93076 [article]

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Explanation for the seam line discontinuity in terrestrial laser scanner point clouds / Derek D. Lichti in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 59 - 69 Titre : Explanation for the seam line discontinuity in terrestrial laser scanner point clouds Type de document : Article/Communication Auteurs : Derek D. Lichti, Auteur ; Craig L. Glennie, Auteur ; Kaleel Al-Durgham, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 59 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] angle de visée [Termes descripteurs IGN] discontinuité [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] télémétrie laser terrestre Résumé : (Auteur) The so-called seam line discontinuity is a phenomenon that can be observed in point clouds captured with some panoramic terrestrial laser scanners. It is an angular discontinuity that is most apparent where the lower limit of the instrument’s angular field-of-view intersects the ground. It appears as step discontinuities at the start (0° horizontal direction) and end (180°) of scanning. To the authors’ best knowledge, its cause and its impact, if any, on point cloud accuracy have not yet been reported. This paper presents the results of a rigorous investigation into several hypothesized causes of this phenomenon: differences between the lower and upper elevation angle scanning limits; the presence of a vertical circle index error; and changes in levelling during scanning. New models for the angular observations have been developed and simulations were performed to independently study the impact of each hypothesized cause and to guide the analyses of real datasets. In order to scrutinize each of the hypothesized causes, experiments were conducted with seven real datasets captured with six different instruments: one hybrid-architecture scanner and five panoramic scanners, one of which was also operated as a hybrid instrument. This study concludes that the difference between the elevation angle scanning limits is the source of the seam line discontinuity phenomenon. Accuracy assessment experiments over real data captured in an indoor test facility demonstrate that the seam line discontinuity has no metric impact on the point clouds. Numéro de notice : A2019-264 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.012 date de publication en ligne : 06/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.012 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93078 [article]

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Modelling of buildings from aerial LiDAR point clouds using TINs and label maps / Minglei Li in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Semantic segmentation of road furniture in mobile laser scanning data / Fashuai Li in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Comparison of three algorithms to estimate tree stem diameter from terrestrial laser scanner data / Joris Ravaglia in Forests, vol 10 n° 7 (July 2019)  

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Empirical stochastic model of detected target centroids: Influence on registration and calibration of terrestrial laser scanners / Tomislav Medic in Journal of applied geodesy, vol 13 n° 3 (July 2019)  

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Structural segmentation and classification of mobile laser scanning point clouds with large variations in point density / Yuan Li in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)  

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Using LiDAR-modified topographic wetness index, terrain attributes with leaf area index to improve a single-tree growth model in south-eastern Finland / Cheikh Mohamedou in Forestry, an international journal of forest research, vol 92 n° 3 (July 2019)  

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RegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

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Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network / Jianfeng Huang in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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Automatic reconstruction of fully volumetric 3D building models from oriented point clouds / Sebastian Ochmann in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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Detecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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