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A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms / Ibrahim Fayad in Remote sensing of environment, vol 265 (November 2021)
[article]
Titre : A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms Type de document : Article/Communication Auteurs : Ibrahim Fayad, Auteur ; Dino Lenco, Auteur ; Nicolas Baghdadi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112652 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Eucalyptus (genre)
[Termes IGN] forme d'onde
[Termes IGN] Global Ecosystem Dynamics Investigation lidar
[Termes IGN] hauteur des arbres
[Termes IGN] modèle de croissance végétale
[Termes IGN] semis de points
[Termes IGN] volume en boisRésumé : (auteur) Full waveform (FW) LiDAR systems have proven their effectiveness to map forest biophysical variables in the last two decades, owing to their ability of measuring, with high accuracy, forest vertical structures. The Global Ecosystem Dynamics Investigation (GEDI) system on board the International Space Station (ISS) is the latest FW spaceborne LiDAR instrument for the continuous observation of Earth's forests. FW systems rely on very sophisticated pre-processing steps to generate a priori metrics in order to leverage their capabilities for the accurate estimation of the aforementioned forest characteristics. The ever-expanding volume of acquired GEDI data, which to date comprises more than 25 billion acquired unfiltered shots, and along with the pre-processed data, amounting to more than 90 TB of data, raises new challenges in terms of adapted preprocessing methods for the suitable exploitation of such a huge and complex amount of LiDAR data. To overcome the issues related to the generation of relevant metrics from GEDI data, we propose a new metric-free approach to estimate canopy dominant heights (Hdom) and wood volume (V) of Eucalyptus plantations over five different regions in Brazil. To avoid metric computation, we leverage deep learning techniques and, more in detail, convolutional neural networks with the aim to analyze the GEDI Level 1B geolocated waveforms. Performance comparisons were conducted between four convolutional neural network (CNN) variants using GEDI waveform data (either untouched, or subsetted) and a metric based Random Forest regressor (RF). Additionally, we tested if our framework can improve the generalization of the models to different distant regions. First, the models were trained using data from all the study regions. Cross validated results showed that the CNN based models compared well against their RF counterpart for both Hdom and V. The RMSE on the estimation of Hdom from the CNN based models varied between 1.54 and 1.94 m with a coefficient of determination (R2) between 0.86 and 0.91, while the RF model produced an accuracy on Hdom estimates of 1.45 m (R2 = 0.92). For V, CNN based estimations ranged from 27.76 to 33.33 m3.ha−1 (R2 between 0.82 and 0.88), while for RF, the RMSE was 27.61 m3.ha−1 (R2 = 0.88). Next, model generalization was assessed by means of a spatial transfer experiment. For Hdom, both the CNN and RF approaches showed similar performances to a global model, however, the CNN based approach showed higher variability on the estimation accuracy, and the variability was related to the forest structure between the trained and tested data (similar tree heights yield better accuracies). For the estimation of V, considering both approaches, the accuracy was dependent on the allometric relationship between Hdom and V in the training and testing regions while lower accuracies on V were obtained when the testing and training regions exhibited a different allometric relationship. Numéro de notice : A2021-869 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112652 Date de publication en ligne : 31/08/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99118
in Remote sensing of environment > vol 265 (November 2021) . - n° 112652[article]Diffuse attenuation coefficient (Kd) from ICESat-2 ATLAS spaceborne Lidar using random-forest regression / Forrest Corcoran in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)
[article]
Titre : Diffuse attenuation coefficient (Kd) from ICESat-2 ATLAS spaceborne Lidar using random-forest regression Type de document : Article/Communication Auteurs : Forrest Corcoran, Auteur ; Christopher E. Parrish, Auteur Année de publication : 2021 Article en page(s) : pp 831 - 840 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] arbre de décision
[Termes IGN] capteur spatial
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forme d'onde
[Termes IGN] littoral
[Termes IGN] modèle de régression
[Termes IGN] semis de points
[Termes IGN] turbidité des eauxRésumé : (Auteur) This study investigates a new method for measuring water turbidity—specifically, the diffuse attenuation coefficient of downwelling irradiance Kd —using data from a spaceborne, green-wavelength lidar aboard the National Aeronautics and Space Administration's ICESat-2 satellite. The method enables us to fill nearshore data voids in existing Kd data sets and provides a more direct measurement approach than methods based on passive multispectral satellite imagery. Furthermore, in contrast to other lidar-based methods, it does not rely on extensive signal processing or the availability of the system impulse response function, and it is designed to be applied globally rather than at a specific geographic location. The model was tested using Kd measurements from the National Oceanic and Atmospheric Administration's Visible Infrared Imaging Radiometer Suite sensor at 94 coastal sites spanning the globe, with Kd values ranging from 0.05 to 3.6 m –1 . The results demonstrate the efficacy of the approach and serve as a benchmark for future machine-learning regression studies of turbidity using ICESat-2. Numéro de notice : A2021-896 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00013R2 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.14358/PERS.21-00013R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99272
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 11 (November 2021) . - pp 831 - 840[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021111 SL Revue Centre de documentation Revues en salle Disponible Footprint size design of large-footprint full-waveform LiDAR for forest and topography applications: A theoretical study / Xuebo Yang in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)
[article]
Titre : Footprint size design of large-footprint full-waveform LiDAR for forest and topography applications: A theoretical study Type de document : Article/Communication Auteurs : Xuebo Yang, Auteur ; Cheng Wang, Auteur ; Xiaohuan Xi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 9745 - 9757 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] empreinte
[Termes IGN] extraction de la végétation
[Termes IGN] forme d'onde pleine
[Termes IGN] hauteur des arbres
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] onde lidar
[Termes IGN] processus gaussien
[Termes IGN] signal lidarRésumé : (auteur) LiDAR footprint, defined as the illumination area of LiDAR sensor on the ground, is the fundamental unit that the sensor collects information from. The design of footprint size crucially influences the acquired LiDAR signals. For large-footprint full-waveform LiDAR, a well-designed footprint size is indispensable to acquire accurate and complete vertical profiles of scene targets. The methods that design the footprint size are increasingly needed to satisfy various application requirements. In this study, an analytical method to designing the footprint size is proposed for forest and topography applications. It is established based on a mixture Gaussian model and the designed footprint size ensures the signals of vegetation and ground can be completely extracted. Experiment results with our method show that the footprint size is preferably in the range of 10.6–25.0 m for forest application, while it is less than 32.3 m for topography application. The intersection of the two sets satisfies both applications. Furthermore, a series of sensibility studies were performed to analyze the influence of multiple key parameters to the optimal footprint size, including the scene characteristics, instrumental configurations, and application requirements. This study provides a theoretical basis for the design of future large-footprint full-waveform laser altimeters. Numéro de notice : A2021-812 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3054324 Date de publication en ligne : 08/02/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3054324 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98885
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 11 (November 2021) . - pp 9745 - 9757[article]A method of extracting high-accuracy elevation control points from ICESat-2 altimetry data / Binbin Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)
[article]
Titre : A method of extracting high-accuracy elevation control points from ICESat-2 altimetry data Type de document : Article/Communication Auteurs : Binbin Li, Auteur ; Huan Xie, Auteur ; Shijie Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 821 - 830 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] altimétrie satellitaire par laser
[Termes IGN] contour
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Etats-Unis
[Termes IGN] grande échelle
[Termes IGN] modèle numérique de surface
[Termes IGN] Nouvelle-Zélande
[Termes IGN] photon
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Due to its high ranging accuracy, spaceborne laser altimetry technology can improve the accuracy of satellite stereo mapping without ground control points. In the past, full-waveform ICE, CLOUD, and Land Elevation Satellite (ICESat) laser altimeter data have been used as one of the main data sources for global elevation control. As a second-generation satellite, ICESat-2 is equipped with an altimeter using photon counting mode. This can further improve the application capability for stereo mapping because of the six laser beams with high along-track repetition frequency, which can provide more detailed ground contour descriptions. Previous studies have addressed how to extract high-accuracy elevation control points from ICESat data. However, these methods cannot be directly applied to ICESat-2 data because of the different modes of the laser altimeters. Therefore, in this paper, we propose a method using comprehensive evaluation labels that can extract high-accuracy elevation control points that meet the different level elevation accuracy requirements for large scale mapping from the ICESat-2 land-vegetation along-track product. The method was verified using two airborne lidar data sets. In flat, hilly, and mountainous areas, by using our method to extract the terrain elevation, the root-mean-square error of elevation control points decrease from 1.249–2.094 m, 2.237–3.225 m, and 2.791–4.822 m to 0.262–0.429 m, 0.484–0.596 m, and 0.611–1.003 m, respectively. The results show that the extraction elevations meet the required accuracy for large scale mapping. Numéro de notice : A2021-895 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00009R2 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.14358/PERS.21-00009R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99271
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 11 (November 2021) . - pp 821 - 830[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021111 SL Revue Centre de documentation Revues en salle Disponible Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features / Bai Zhu in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)
[article]
Titre : Robust registration of aerial images and LiDAR data using spatial constraints and Gabor structural features Type de document : Article/Communication Auteurs : Bai Zhu, Auteur ; Yuanxin Ye, Auteur ; Liang Zhou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 129 - 147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] correction géométrique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] élément d'orientation externe
[Termes IGN] enregistrement de données
[Termes IGN] filtre de Gabor
[Termes IGN] image aérienne
[Termes IGN] recalage d'image
[Termes IGN] semis de points
[Termes IGN] SIFT (algorithme)
[Termes IGN] structure-from-motionRésumé : (auteur) Co-registration of aerial imagery and Light Detection and Ranging (LiDAR) data is quite challenging because the different imaging mechanisms produce significant geometric and radiometric distortions between the two multimodal data sources. To address this problem, we propose a robust and effective coarse-to-fine registration method that is conducted in two stages utilizing spatial constraints and Gabor structural features. In the first stage, the LiDAR point cloud data is transformed into an intensity map that is used as the reference image. Then, coarse registration is completed by designing a partition-based Features from Accelerated Segment Test (FAST) operator to extract the uniformly distributed interest points in the aerial images and thereafter performing a local geometric correction based on the collinearity equations using the exterior orientation parameters (EoPs). The coarse registration aims to provide a reliable spatial geometry relationship for the subsequent fine registration and is designed to eliminate rotation and scale changes, as well as making only a few translation differences exist between the images. In the second stage, a novel feature descriptor called multi-Scale and multi-Directional Features of odd Gabor (SDFG) is first built to capture the multi-scale and multi-directional structural properties of the images. Then, the three-dimensional (3D) phase correlation (PC) of the SDFG descriptor is established to detect the control points (CPs) between the aerial and LiDAR intensity image in the frequency domain, where the image matching is accelerated by the 3D Fast Fourier Transform (FFT) technique. Finally, the obtained CPs not only are employed to refine the EoPs, but also are used to achieve the fine registration of the aerial images and LiDAR data. We conduct experiments to verify the robustness of the proposed registration method using three sets of aerial images and LiDAR data with different scene coverage. Experimental results show that the proposed method is robust to geometric distortions and radiometric changes. Moreover, it achieves the registration accuracy of less than 2 pixels for all cases, which outperforms the current four state-of-the-art methods, demonstrating its superior registration performance. Numéro de notice : A2021-773 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.09.010 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98830
in ISPRS Journal of photogrammetry and remote sensing > Vol 181 (November 2021) . - pp 129 - 147[article]Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region / Paulo Victor N. Araújo in Natural Hazards and Earth System Sciences, vol 21 n° 11 (November 2021)PermalinkTowards the empirical determination of correlations in terrestrial laser scanner range observations and the comparison of the correlation structure of different scanners / Berit Schmitz in ISPRS Journal of photogrammetry and remote sensing, Vol 182 (December 2021)PermalinkUsing LiDAR and Random Forest to improve deer habitat models in a managed forest landscape / Colin S. Shanley in Forest ecology and management, vol 499 (November-1 2021)PermalinkUtilisation de l’apprentissage profond dans la modélisation 3D urbaine : partie 2, post-traitement et évaluation / Hamza Ben Addou in Géomatique expert, n° 136 (novembre - décembre 2021)PermalinkA vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)PermalinkComparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada / Bernadett Dobre in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkImpact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests / Meinrad Abegg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)PermalinkLeast squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)PermalinkLinear regression and lines intersecting as a method of extracting punctual entities in a lidar point cloud / Marlo Antonio Ribeiro Martins in Boletim de Ciências Geodésicas, vol 27 n° 3 ([01/10/2021])PermalinkA methodology for producing realistic hill-shading map based on shaded relief map, digital orthophotographic map fusion and IHS transformation / Hongyun Zeng in Annals of GIS, vol 27 n° 4 (October 2021)PermalinkStand delineation based on laser scanning data and simulated annealing / Yusen Sun in European Journal of Forest Research, vol 140 n° 5 (October 2021)PermalinkUrban geospatial information acquisition mobile mapping system based on close-range photogrammetry and IGS site calibration / Ming Guo in Geo-spatial Information Science, vol 24 n° 4 (October 2021)PermalinkAerial and UAV images for photogrammetric analysis of Belvedere Glacier evolution in the period 1977–2019 / Carlo Lapige De Gaetani in Remote sensing, vol 13 n° 18 (September-2 2021)PermalinkMapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)Permalink3D map creation using crowdsourced GNSS data / Terence Lines in Computers, Environment and Urban Systems, vol 89 (September 2021)PermalinkCombining photogrammetric and bathymetric data to build a 3D model of a canal tunnel / Emmanuel Moisan in Photogrammetric record, Vol 36 n° 175 (September 2021)PermalinkA comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations / Irfan A. Iqbal in Remote sensing, vol 13 n° 17 (September-1 2021)PermalinkDouble adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkGaussian mixture model of ground filtering based on hierarchical curvature constraints for airborne Lidar point clouds / Longjie Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkLarge-area inventory of species composition using airborne laser scanning and hyperspectral data / Hans Ole Ørka in Silva fennica, vol 55 n° 4 (September 2021)PermalinkA new approach for the development of grid models calculating tropospheric key parameters over China / Ge Zhu in Remote sensing, vol 13 n° 17 (September-1 2021)PermalinkProtection naturelle contre la submersion, apport de l'intelligence artificielle / Antoine Mury in Cartes & Géomatique, n° 245-246 (septembre - décembre 2021)PermalinkRelevés de la grotte Cosquer : partie 1, la grotte, les premiers relevés, un monument et une histoire chaotiques / Bertrand Chazaly in XYZ, n° 168 (septembre 2021)PermalinkRelevés de la grotte Cosquer : partie 2, vers une dématérialisation de la grotte par digitalisation des processus et numérisations 3D, comment offrir à la communauté scientifique et au grand public l’accès au plus inaccessible des grands sanctuaires ornés d’Europe / Bertrand Chazaly in XYZ, n° 168 (septembre 2021)PermalinkShining light on danger / Anonyme in GEO: Geoconnexion international, Vol 20 n° 5 (Autumn 2021)PermalinkTarget-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)PermalinkUtilisation de l'apprentissage profond dans la modélisation 3D urbaine [Partie 1] / Hamza Ben Addou in Géomatique expert, n° 135 (septembre 2021)PermalinkMeasuring shallow-water bathymetric signal strength in lidar point attribute data using machine learning / Kim Lowell in International journal of geographical information science IJGIS, vol 35 n° 8 (August 2021)PermalinkStructure-aware indoor scene reconstruction via two levels of abstraction / Hao Fang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkSurface modelling of forest aboveground biomass based on remote sensing and forest inventory data / Xiaofang Sun in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkLeaf and wood separation for individual trees using the intensity and density data of terrestrial laser scanners / Kai Tan in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkDetecting structural changes induced by Heterobasidion root rot on Scots pines using terrestrial laser scanning / Timo P Pitkänen in Forest ecology and management, vol 492 (July-15 2021)PermalinkAn adaptive filtering algorithm of multilevel resolution point cloud / Youyuan Li in Survey review, Vol 53 n° 379 (July 2021)PermalinkDeformation analysis of a reference wall towards the uncertainty investigation of terrestrial laser scanners / Berit Schmitz in Journal of applied geodesy, vol 15 n° 3 (July 2021)PermalinkExtracting Shallow-Water Bathymetry from Lidar point clouds using pulse attribute data: Merging density-based and machine learning approaches / Kim Lowell in Marine geodesy, vol 44 n° 4 (July 2021)PermalinkLa géovisualisation de données massives sur le Web : entre avancées technologiques et évolutions cartographiques / Boris Mericskay in Mappemonde, n° 131 (juillet 2021)PermalinkIntegration of cadastral survey data into building information models / Behnam Atazadeh in Geo-spatial Information Science, vol 24 n° 3 (July 2021)PermalinkLayout graph model for semantic façade reconstruction using laser point clouds / Hongchao Fan in Geo-spatial Information Science, vol 24 n° 3 (July 2021)PermalinkThree-dimensional reconstruction of single input image based on point cloud / Yu Hou in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)PermalinkUpdating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data / Niels Lindgren in Scandinavian journal of forest research, vol 36 n° 5 ([01/07/2021])PermalinkVectorized indoor surface reconstruction from 3D point cloud with multistep 2D optimization / Jiali Han in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)PermalinkFast weakly supervised detection of railway-related infrastructures in lidar acquisitions / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)PermalinkIndividual tree extraction from UAV lidar point clouds based on self-adaptive mean shift segmentation / Zhenyang Hui in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-1-2021 (July 2021)PermalinkRoadside tree extraction and diameter estimation with MMS lidar by using point-cloud image / Genki Takahashi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)PermalinkTowards efficient indoor/outdoor registration using planar polygons / Rahima Djahel in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)Permalink3D reconstruction of bridges from airborne laser scanning data and cadastral footprints / Steffen Goebbels in Journal of Geovisualization and Spatial Analysis, vol 5 n° 1 (June 2021)PermalinkAn innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data / Van-Tho Nguyen in Annals of Forest Science, vol 78 n° 2 (June 2021)PermalinkForest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band / Xing Peng in Remote sensing, vol 13 n° 11 (June-1 2021)PermalinkIndividual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)PermalinkModel-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)PermalinkPredicting tree species based on the geometry and density of aerial laser scanning point cloud of treetops / Nina Kranjec in Geodetski vestnik, vol 65 n° 2 (June - August 2021)PermalinkRobust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds / Reza Maalek in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)PermalinkTree height growth modelling using LiDAR-derived topography information / Milan Kobal in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)PermalinkWeak relationships of continuous forest management intensity and remotely sensed stand structural complexity in temperate mountain forests / Thomas Asbeck in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkIntegration of laser scanner and photogrammetry for heritage BIM enhancement / Yahya Alshawabkeh in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)PermalinkSensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment / Maxime Soma in Remote sensing of environment, vol 257 (May 2021)PermalinkDetecting archaeological features with airborne laser scanning in the alpine tundra of Sápmi, Northern Finland / Oula Seitsonen in Remote sensing, vol 13 n° 8 (April-2 2021)PermalinkAn iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects / Linyuan Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkUne analyse de la couverture 5G francilienne avec PostGIS et QGIS / Anonyme in Géomatique expert, n° 134 (avril 2021)PermalinkAutomated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)PermalinkParsing of urban facades from 3D point clouds based on a novel multi-view domain / Wei Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 4 (April 2021)PermalinkTree extraction and estimation of walnut structure parameters using airborne LiDAR data / Javier Estornell in International journal of applied Earth observation and geoinformation, vol 96 (April 2021)PermalinkUtiliser les données maillées sous QGIS / Anonyme in Géomatique expert, n° 134 (avril 2021)PermalinkSRP, une base de calage 3D de très haute précision sur le continent africain / Laure Chandelier in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkTerrestrial laser scanning intensity captures diurnal variation in leaf water potential / S. Junttila in Remote sensing of environment, Vol 255 (March 2021)Permalink3D change detection using adaptive thresholds based on local point cloud density / Dan Liu in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)PermalinkEnhanced trajectory estimation of mobile laser scanners using aerial images / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)PermalinkGraph convolutional autoencoder model for the shape coding and cognition of buildings in maps / Xiongfeng Yan in International journal of geographical information science IJGIS, vol 35 n° 3 (March 2021)PermalinkImproving the unsupervised mapping of riparian bugweed in commercial forest plantations using hyperspectral data and LiDAR / Kabir Peerbhay in Geocarto international, vol 36 n° 4 ([01/03/2021])PermalinkOntology-based semantic conceptualisation of historical built heritage to generate parametric structured models from point clouds / Elisabetta Colucci in Applied sciences, vol 11 n° 6 (March 2021)PermalinkProgressive TIN densification with connection analysis for urban Lidar data / Tao Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 3 (March 2021)PermalinkWhat factors shape spatial distribution of biomass in riparian forests? Insights from a LiDAR survey over a large area / Leo Huylenbroeck in Forests, vol 12 n° 3 (March 2021)PermalinkAn anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds / Fei Su in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)PermalinkAutomatic filtering and 2D modeling of airborne laser scanning building point cloud / Fayez Tarsha-Kurdi in Transactions in GIS, Vol 25 n° 1 (February 2021)PermalinkCurved buildings reconstruction from airborne LiDAR data by matching and deforming geometric primitives / Jingwei Song in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)PermalinkDeveloping a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data / Juan Guerra-Hernández in Forest ecology and management, vol 481 (February 2021)PermalinkA feature-preserving point cloud denoising algorithm for LiDAR-derived DEM construction / Chuanfa Chen in Survey review, Vol 53 n° 377 (February 2021)PermalinkImproving trajectory estimation using 3D city models and kinematic point clouds / Lucas Lucks in Transactions in GIS, Vol 25 n° 1 (February 2021)PermalinkMonitoring the coastal changes of the Po river delta (Northern Italy) since 1911 using archival cartography, multi-temporal aerial photogrammetry and LiDAR data: implications for coastline changes in 2100 A.D. / Massimo Fabris in Remote sensing, Vol 13 n° 3 (February 2021)PermalinkTropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning / Maryam Pourshamsi in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)PermalinkA density-based algorithm for the detection of individual trees from LiDAR data / Melissa Latella in Remote sensing, Vol 13 n° 2 (January-2 2021)PermalinkPermalink3D urban scene understanding by analysis of LiDAR, color and hyperspectral data / David Duque-Arias (2021)PermalinkAcquisition lasergrammétrique d’ouvrages d’art pour l’interopérabilité BIM-SIG, cas pratique du syndicat mixte "Routes de Guadeloupe" / Sonia Sermanson (2021)PermalinkPermalinkAn efficient representation of 3D buildings: application to the evaluation of city models / Oussama Ennafii (2021)PermalinkApplications of remote sensing data in mapping of forest growing stock and biomass / Jose Aranha (2021)PermalinkApport des méthodes : imagerie drone, LiDAR et imagerie hyperspectrale pour l’étude du littoral vendéen / Mathis Baudis (2021)PermalinkApport de la photogrammétrie et de l’intelligence artificielle à la détection des zones amiantées sur les fronts rocheux / Philippe Caudal (2021)PermalinkPermalinkAutomatic object extraction from airborne laser scanning point clouds for digital base map production / Elyta Widyaningrum (2021)PermalinkPermalinkBuilding extraction from Lidar data using statistical methods / Haval Abdul-Jabbar Sadeq in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)PermalinkCalcul de la largeur à pleins bords de grands cours d’eau à partir de MNT LiDAR / Nicolas Fermen (2021)PermalinkCombining deep learning and mathematical morphology for historical map segmentation / Yizi Chen (2021)PermalinkContributions to graph-based hierarchical analysis for images and 3D point clouds / Leonardo Gigli (2021)PermalinkConvex hull: another perspective about model predictions and map derivatives from remote sensing data / Jean-Pierre Renaud (2021)PermalinkCorrection radiométrique et recalage de nuages de points pour la reconstruction tridimensionnelle d'oeuvres du patrimoine culturel / Nathan Sanchiz (2021)PermalinkDeep convolutional neural networks for scene understanding and motion planning for self-driving vehicles / Abdelhak Loukkal (2021)PermalinkDétection d’ouvertures par segmentation sémantique de nuages de points 3D : apport de l’apprentissage profond / Camille Lhenry (2021)PermalinkDétection/reconnaissance d'objets urbains à partir de données 3D multicapteurs prises au niveau du sol, en continu / Younes Zegaoui (2021)PermalinkDétection et reconstruction 3D d’arbres urbains par segmentation de nuages de points : apport de l’apprentissage profond / Victor Alteirac (2021)PermalinkPermalinkPermalinkÉtude sur la réalisation d’un levé d’intérieur par photogrammétrie via un smartphone / Maxence Augé (2021)PermalinkPermalinkPermalinkExtraction of street pole-like objects based on plane filtering from mobile LiDAR data / Jingming Tu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)PermalinkFOSTER - An R package for forest structure extrapolation / Martin Queinnec in Plos one, vol 16 n° 1 (January 2021)PermalinkFusion of ground penetrating radar and laser scanning for infrastructure mapping / Dominik Merkle in Journal of applied geodesy, vol 15 n° 1 (January 2021)PermalinkGeometric computer vision: omnidirectional visual and remotely sensed data analysis / Pouria Babahajiani (2021)PermalinkGeoreferencing 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)PermalinkHow do users interact with Virtual Geographic Environments? Users’ behavior evaluation in urban participatory planning / Thibaud Chassin (2021)PermalinkImproving GEDI footprint geolocation using a high resolution digital terrain model / Anouk Schleich (2021)PermalinkPermalinkPermalinkPermalinkOptimisation des protocoles de numérisation 3D multi-capteurs et de fusion de données hétérogènes au sein de l'entreprise Premier plan / Elisa Gautron (2021)PermalinkQualification des données LiDAR GEDI pour le suivi de l’impact climatique sur la forêt de Südharz / Iris Jeuffrard (2021)PermalinkReconnaissance spécifique et cartographie des arbres de la canopée en forêt tropicale en Guyane française par fusion de données lidar et hyperspectrales appliquées aux besoins de la gestion forestière / Anthony Laybros (2021)PermalinkRelation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds / Yuan Li in Remote sensing, vol 13 n° 1 (January-1 2021)PermalinkPermalinkRemote sensing analysis of small scale dynamic phenomena in the atmospheric boundary layer / Kostas Cheliotis (2021)PermalinkPermalinkPermalinkPermalinkStructure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring / Edoardo Grottoli in Remote sensing, vol 13 n° 1 (January-1 2021)PermalinkPermalinkTélédétection synchronisée hyperspectrale et LiDAR à retour d’onde complet : application au suivi des littoraux sableux de la région Pays-de-la-Loire / Giovanni Frati (2021)PermalinkThe potential of LiDAR and UAV-photogrammetric data analysis to interpret archaeological sites: A case study of Chun Castle in South-West England / Israa Kadhim in ISPRS International journal of geo-information, vol 10 n° 1 (January 2021)PermalinkTraitements et acquisitions de données lasergrammétriques, topométriques et topographiques / Théo Paille (2021)PermalinkUnit-level small area estimation of forest inventory with GEDI auxiliary information / Shaohui Zhang (2021)PermalinkUnit-level small area estimation of forest inventory with GEDI auxiliary information in France / Shaohui Zhang (2021)PermalinkA valuable model ? / Alexis Debray in GEO: Geoconnexion international, vol 20 n° 1 (January - February 2021)PermalinkVegetation stratum occupancy prediction from airborne LiDAR 3D point clouds / Ekaterina Kalinicheva (2021)PermalinkVolumes by tree species can be predicted using photogrammetric UAS data, Sentinel-2 images and prior field measurements / Mikko Kukkonen in Silva fennica, vol 55 n° 1 (January 2021)PermalinkAdjusting the regular network of squares resolution to the digital terrain model surface shape / Dariusz Gościewski in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)PermalinkDu drone LiDAR à un nuage de points précis et exact : une chaîne de traitement LiDAR adaptée et quasi automatique / Maxime Lafleur in XYZ, n° 165 (décembre 2020)PermalinkMS-RRFSegNetMultiscale regional relation feature segmentation network for semantic segmentation of urban scene point clouds / Haifeng Luo in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)PermalinkRemote sensing in urban planning: Contributions towards ecologically sound policies? / Thilo Wellmann in Landscape and Urban Planning, vol 204 (December 2020)PermalinkLes stations virtuelles au service de la cartographie mobile / Mathieu Regul in XYZ, n° 165 (décembre 2020)PermalinkThe utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland / Ranjith Gopalakrishnan in Annals of Forest Science, vol 77 n° 4 (December 2020)PermalinkActive and incremental learning for semantic ALS point cloud segmentation / Yaping Lin in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkBuilding change detection using a shape context similarity model for LiDAR data / Xuzhe Lyu in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkBuilding facade reconstruction using crowd-sourced photos and two-dimensional maps / Wu Jie in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 11 (November 2020)PermalinkEffects of radiometric correction on cover type and spatial resolution for modeling plot level forest attributes using multispectral airborne LiDAR data / Wai Yeung Yan in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkIndoor point cloud segmentation using iterative Gaussian mapping and improved model fitting / Bufan Zhao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)PermalinkIs field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest / Luka Jurjević in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)PermalinkTopographic connection method for automated mapping of landslide inventories, study case: semi urban sub-basin from Monterrey, Northeast of México / Nelly L. Ramirez Serrato in Geocarto international, vol 35 n° 15 ([01/11/2020])PermalinkAssessing the effects of thinning on stem growth allocation of individual Scots pine trees / Ninni Saarinen in Forest ecology and management, vol 474 ([15/10/2020])PermalinkComparing features of single and multi-photon lidar in boreal forests / Xiaowei Yu in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)PermalinkGEBCO Gridded Bathymetric Datasets for mapping Japan Trench geomorphology by means of GMT scripting toolset / Polina Lemenkova in Geodesy and cartography, vol 46 n° 3 (October 2020)PermalinkGoing to the Finnish line / Hannu Heinonen in GEO: Geoconnexion international, vol 19 n° 6 (October 2020)PermalinkHierarchical instance recognition of individual roadside trees in environmentally complex urban areas from UAV laser scanning point clouds / Yongjun Wang in ISPRS International journal of geo-information, vol 9 n° 10 (October 2020)PermalinkA LiDAR aiding ambiguity resolution method using fuzzy one-to-many feature matching / Chuang Qian in Journal of geodesy, vol 94 n° 10 (October 2020)PermalinkSee the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning / Zhouxin Xi in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)PermalinkThe effect of leaf-on and leaf-off forest canopy conditions on LiDAR derived estimations of forest structural diversity / Sophie Davison in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)PermalinkTowards an optimization of sample plot size and scanner position layout for terrestrial laser scanning in multi-scan mode / Tim Ritter in Forests, vol 11 n° 10 (October 2020)PermalinkTree species classification using structural features derived from terrestrial laser scanning / Louise Terryn in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)PermalinkWeighted spherical sampling of point clouds for forested scenes / Alex Fafard in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)PermalinkApplication of UAV photogrammetry with LiDAR data to facilitate the estimation of tree locations and DBH values for high-value timber species in Northern Japanese mixed-wood forests / Kyaw Thu Moe in Remote sensing, vol 12 n° 17 (September-1 2020)PermalinkLocal terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)PermalinkRelevé 3D et classification de nuages de points de patrimoine bâti / Arnadi Murtiyoso in XYZ, n° 164 (septembre 2020)PermalinkShallow water bathymetry derived from green wavelength terrestrial laser scanner / Theodore Panagou in Marine geodesy, Vol 43 n° 5 (September 2020)PermalinkPlanar polygons detection in lidar scans based on sensor topology enhanced Ransac / Stéphane Guinard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkProvably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkAssessment of USGS DEMs for modelling pothole inundation in the prairie pothole region of Iowa / Priyadarshi Upadhyay in Geocarto international, vol 35 n° 9 ([01/07/2020])PermalinkClassification of hyperspectral and LiDAR data using coupled CNNs / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkRoles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects / Jike Chen in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)PermalinkUnsupervised semantic and instance segmentation of forest point clouds / Di Wang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkAn integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkEstimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkHétérogénéité des distances : quel impact sur la qualité des relevés lidar aériens et terrestres ? / Laurent Polidori in XYZ, n° 163 (juin 2020)PermalinkMapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors / Svetlana Saarela in Forest ecosystems, vol 7 (2020)PermalinkMapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)PermalinkMining spatiotemporal association patterns from complex geographic phenomena / Zhanjun He in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)PermalinkModélisation d'une maquette sur la base de données LiDAR et intégration d'un projet 3D / Julien Brunner in Géomatique suisse, vol 118 n° 6 (juin 2020)PermalinkUnder-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkAssessment of the accuracy of DTM river bed model using classical surveying measurement and LiDAR: a case study in Poland / Pawel Kotlarz in Survey review, vol 52 n° 372 (May 2020)PermalinkAutomated conflation of digital elevation model with reference hydrographic lines / Timofey Samsonov in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)PermalinkExploring the potential of deep learning segmentation for mountain roads generalisation / Azelle Courtial in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)PermalinkFiltering of airborne LiDAR bathymetry based on bidirectional cloth simulation / Anxiu Yang in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkFusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)PermalinkImproved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests / Sruthi M. Krishna Moorthy in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkMapping urban grey and green structures for liveable cities using a 3D enhanced OBIA approach and vital statistics / E. Banzhaf in Geocarto international, vol 35 n° 6 ([01/05/2020])PermalinkMethod for extraction of airborne LiDAR point cloud buildings based on segmentation / Maohua Liu in Plos one, vol 15 n° 5 (May 2020)PermalinkOutlier detection and robust plane fitting for building roof extraction from LiDAR data / Emon Kumar Dey in International Journal of Remote Sensing IJRS, vol 41 n° 16 (01-10 May 2020)PermalinkLa télédétection aéroportée pour la gestion des territoires forestiers de montagne / Jean-Matthieu Monnet in Sciences, eaux & territoires, n° 33 (avril 2020)PermalinkDirectionally constrained fully convolutional neural network for airborne LiDAR point cloud classification / Congcong Wen in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkMonitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkMultitemporal analysis of gully erosion in olive groves by means of digital elevation models obtained with aerial photogrammetric and LIDAR data / Tomás Fernández in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkUsing multi-scale and hierarchical deep convolutional features for 3D semantic classification of TLS point clouds / Zhou Guo in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)PermalinkHow far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study / Enrico Borgogno Mondino in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)Permalink3D laser scanning of the natural caves: Example of Škocjanske jame / Richard Walters in Geodetski vestnik, Vol 64 n° 1 (March - May 2020)PermalinkAn IEEE value loop of human-technology collaboration in geospatial information science / Liqiu Meng in Geo-spatial Information Science, vol 23 n° 1 (March 2020)Permalink