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Classification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 1 (January-1 2022) . - n° 199 Titre : Classification of mediterranean shrub species from UAV point clouds Type de document : Article/Communication Auteurs : Juan Pedro Carbonell-Rivera, Auteur ; Jesus Torralba, Auteur ; Javier Estornell, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 199 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] apprentissage automatique [Termes IGN] arbuste [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par Perceptron multicouche [Termes IGN] Espagne [Termes IGN] Extreme Gradient Machine [Termes IGN] forêt méditerranéenne [Termes IGN] image captée par drone [Termes IGN] incendie de forêt [Termes IGN] indice de végétation [Termes IGN] modèle de simulation [Termes IGN] modèle numérique de terrain [Termes IGN] parc naturel [Termes IGN] photogrammétrie aérienne [Termes IGN] semis de points Résumé : (auteur) Modelling fire behaviour in forest fires is based on meteorological, topographical, and vegetation data, including species’ type. To accurately parameterise these models, an inventory of the area of analysis with the maximum spatial and temporal resolution is required. This study investigated the use of UAV-based digital aerial photogrammetry (UAV-DAP) point clouds to classify tree and shrub species in Mediterranean forests, and this information is key for the correct generation of wildfire models. In July 2020, two test sites located in the Natural Park of Sierra Calderona (eastern Spain) were analysed, registering 1036 vegetation individuals as reference data, corresponding to 11 shrub and one tree species. Meanwhile, photogrammetric flights were carried out over the test sites, using a UAV DJI Inspire 2 equipped with a Micasense RedEdge multispectral camera. Geometrical, spectral, and neighbour-based features were obtained from the resulting point cloud generated. Using these features, points belonging to tree and shrub species were classified using several machine learning methods, i.e., Decision Trees, Extra Trees, Gradient Boosting, Random Forest, and MultiLayer Perceptron. The best results were obtained using Gradient Boosting, with a mean cross-validation accuracy of 81.7% and 91.5% for test sites 1 and 2, respectively. Once the best classifier was selected, classified points were clustered based on their geometry and tested with evaluation data, and overall accuracies of 81.9% and 96.4% were obtained for test sites 1 and 2, respectively. Results showed that the use of UAV-DAP allows the classification of Mediterranean tree and shrub species. This technique opens a wide range of possibilities, including the identification of species as a first step for further extraction of structure and fuel variables as input for wildfire behaviour models. Numéro de notice : A2022-057 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14010199 En ligne : https://doi.org/10.3390/rs14010199 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99462 [article]

Tree 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)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 96 (April 2021) . - n° 102273 Titre : Tree extraction and estimation of walnut structure parameters using airborne LiDAR data Type de document : Article/Communication Auteurs : Javier Estornell, Auteur ; Edyta Hadas, Auteur ; J. Marti, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 102273 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] classification par nuées dynamiques [Termes IGN] dendrométrie [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Espagne [Termes IGN] extraction d'arbres [Termes IGN] houppier [Termes IGN] Juglans regia [Termes IGN] modèle numérique de terrain [Termes IGN] plantation agricole [Termes IGN] semis de points Résumé : (auteur) The development of new tools based on remote sensing data in agriculture contributes to cost reduction, increased production, and greater profitability. Airborne LiDAR (Light Detection and Ranging) data show a significant potential for geometrically characterizing tree plantations. This study aims to develop a methodology to extract walnut (Juglans regia L.) crowns under leafless conditions using airborne LiDAR data. An original approach based on the alpha-shape algorithm, identification of local maxima, and k-means algorithms is developed to extract the crowns of walnut trees in a plot located in Viver (Eastern Spain) with 192 trees. In addition, stem diameter and volume, crown diameter, total height, and crown height were estimated from cloud metrics and other 2D parameters such as crown area, and diameter derived from LiDAR data. A correct identification was made of 178 trees (92.7%). For structure parameters, the most accurate results were obtained for crown diameter, stem diameter, and stem volume with coefficient of determination values (R2) equal to 0.95, 0.87 and 0.83; and RMSE values of 0.43 m (5.70%), 0.02 m (9.35%) and 0.016 m3 (21.55%), respectively. The models that gave the lowest R2 values were 0.69 for total height and 0.70 for crown height, with RMSE values of 0.84 m (12.4%) and 0.83 m (14.5%), respectively. A suitable definition of the central and lower parts of tree canopies was observed. Results of this study generate valuable information, which can be applied for improving the management of walnut plantations. Numéro de notice : A2021-239 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102273 Date de publication en ligne : 13/12/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102273 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97265 [article]

Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics / Pablo Crespo-Peremarch in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 453 - 464 Titre : Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics Type de document : Article/Communication Auteurs : Pablo Crespo-Peremarch, Auteur ; Luis Ángel Ruiz, Auteur ; Angel Balaguer-Beser, Auteur ; Javier Estornell, Auteur Année de publication : 2018 Article en page(s) : pp 453 - 464 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Abies grandis [Termes IGN] Acer macrophyllum [Termes IGN] amplitude [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage en vol [Termes IGN] filtrage du bruit [Termes IGN] forme d'onde pleine [Termes IGN] impulsion laser [Termes IGN] lidar à retour d'onde complète [Termes IGN] Oregon (Etats-Unis) [Termes IGN] prétraitement du signal [Termes IGN] Pseudotsuga menziesii [Termes IGN] Thuja plicata [Termes IGN] Tsuga heterophylla [Termes IGN] voxel Résumé : (auteur) LiDAR full-waveform (LFW) pulse density is not homogeneous along study areas due to overlap between contiguous flight stripes and, to a lesser extent, variations in height, velocity and altitude of the platform. As a result, LFW-derived metrics extracted at the same spot but at different pulse densities differ, which is called “side-lap effect”. Moreover, this effect is reflected in forest stand estimates, since they are predicted from LFW-derived metrics. This study was undertaken to analyze LFW-derived metric variations according to pulse density, voxel size and value assignation method in order to reduce the side-lap effect. Thirty LiDAR samples with a minimum density of 16 pulses.m−2 were selected from the testing area and randomly reduced to 2 pulses.m−2 with an interval of 1 pulse.m−2, then metrics were extracted and compared for each sample and pulse density at different voxel sizes and assignation values. Results show that LFW-derived metric variations as a function of pulse density follow a negative exponential model similar to the exponential semivariogram curve, increasing sharply until they reach a certain pulse density, where they become stable. This value represents the minimum pulse density (MPD) in the study area to optimally minimize the side-lap effect. This effect can also be reduced with pulse densities lower than the MPD modifying LFW parameters (i.e. voxel size and assignation value). Results show that LFW-derived metrics are not equally influenced by pulse density, such as number of peaks (NP) and ROUGHness of the outermost canopy (ROUGH) that may be discarded for further analyses at large voxel sizes, given that they are highly influenced by pulse density. In addition, side-lap effect can be reduced by either increasing pulse density or voxel size, or modifying the assignation value. In practice, this leads to a proper estimate of forest stand variables using LFW data. Numéro de notice : A2018-543 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.10.012 Date de publication en ligne : 05/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91569 [article]

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Accuracy of tree geometric parameters depending on the LiDAR data density / Edyta Hadas in European journal of remote sensing, vol 49 n° 1 (2016)  

Public [article]  inEuropean journal of remote sensing > vol 49 n° 1 (2016) . - pp 73 - 92 Titre : Accuracy of tree geometric parameters depending on the LiDAR data density Type de document : Article/Communication Auteurs : Edyta Hadas, Auteur ; Javier Estornell, Auteur Année de publication : 2016 Article en page(s) : pp 73 - 92 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] Olea europaea [Termes IGN] précision géométrique (imagerie) Résumé : (auteur) The aim of this study was to compare geometric parameters of olive trees (tree height,crown base height, crown diameters, crown area), using LiDAR data of different densities: 0.5, 3.5 and 9 points m-2. Two strategies were proposed and verified with a focus on raster and raw data analysis. Statistical tests have shown, that for the tree height and crown base height estimation, the choice of strategy was irrelevant, but denser LiDAR data provided more accurate results. The raster analysis strategy applied for sparse and dense LiDAR datasets allowed crown shape to be determined with a similar accuracy which means raster data are useful for estimating other indirect tree parameters. The quality of results was independent from the tree size. Numéro de notice : A2016-833 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164905 En ligne : http://dx.doi.org/10.5721/EuJRS20164905 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82718 [article]