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Auteur Kai Tan |
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Leaf 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)
[article]
Titre : Leaf and wood separation for individual trees using the intensity and density data of terrestrial laser scanners Type de document : Article/Communication Auteurs : Kai Tan, Auteur ; Weiguo Zhang, Auteur ; Zhen Dong, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7038 - 7050 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] bois
[Termes IGN] densité du feuillage
[Termes IGN] données lidar
[Termes IGN] données TLS (télémétrie)
[Termes IGN] feuille (végétation)
[Termes IGN] réflectance spectrale
[Termes IGN] semis de pointsRésumé : (auteur) Terrestrial laser scanning (TLS) is a highly effective and noninvasive technology for retrieving the structural and biophysical attributes of trees using 3-D high-accuracy and high-density point clouds. The separation of leaf and wood points in TLS data is a prerequisite for the accurate and reliable derivation of these attributes. In this study, a new method is proposed to separate the leaf and wood points of individual trees by combining the TLS radiometric (intensity) and geometric (density) data. The leaf points are separated from the wood ones through three steps. First, the corrected intensity data are used to separate a part of the leaf points preliminarily given the differences in reflectance characteristics. Second, the density data are adopted for the further separation of another part of the leaf points because the density of the remaining leaf points is smaller than that of the wood points. Finally, a connectivity clustering algorithm is conducted to form several clusters with different sizes (points) and the remaining leaf points are separated in accordance with the cluster sizes. Eight different trees are selected to evaluate the performance of the proposed method. The averaged overall accuracy and kappa coefficient of the eight trees are approximately 95% and 0.81, respectively. The results suggest that the combination of TLS intensity and density data can perform a superior separation of leaf and wood points in terms of efficiency and accuracy, and the proposed separation method can be accurately and robustly used for various trees with different species, sizes, and structures. Numéro de notice : A2021-633 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3032167 Date de publication en ligne : 30/10/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3032167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98295
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 8 (August 2021) . - pp 7038 - 7050[article]Estimation of soil surface water contents for intertidal mudflats using a near-infrared long-range terrestrial laser scanner / Kai Tan in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
[article]
Titre : Estimation of soil surface water contents for intertidal mudflats using a near-infrared long-range terrestrial laser scanner Type de document : Article/Communication Auteurs : Kai Tan, Auteur ; Jin Chen, Auteur ; Weiguo Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 129 - 139 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Chine
[Termes IGN] données lidar
[Termes IGN] données TLS (télémétrie)
[Termes IGN] humidité du sol
[Termes IGN] littoral
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] réflectance
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestre
[Termes IGN] teneur en vapeur d'eau
[Termes IGN] vaseRésumé : (Auteur) Estimations of the soil surface water contents and distributions play a key role in the ecological, environmental, and topographical investigations for intertidal mudflats. However, existing techniques have limitations. Long-range terrestrial laser scanners (TLSs) can record the co-located intensity value which refers to a measure of the backscattered laser from each scanned point. Most long-range TLSs emit near-infrared lasers that can be strongly absorbed by water. Thus, the intensity values can be used as proxies for water contents. In this study, the intensity data of long-range TLSs are corrected for the incidence angle and distance effects to quantitatively estimate the soil surface water contents of intertidal mudflats. A case study for a mudflat in Chongming Island, Shanghai, China, is conducted. Results indicate that compared with traditional techniques, the corrected intensity data of long-range TLSs are extremely effective data sources for a quick, accurate, and detailed estimation of water contents for large-area mudflats. The estimation root mean square error is approximately 3%. Furthermore, the 3D distributions of the water contents can be accurately mapped by combining the point cloud of the mudflats to potentially analyze the intrinsic association among water contents and topography, vegetation coverage, and habitation of creatures in mudflats. Numéro de notice : A2020-013 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.isprsjprs.2019.11.003 Date de publication en ligne : 26/11/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.003 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94402
in ISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 129 - 139[article]Exemplaires(3)
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