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Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan / Katsuto Shimizu in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102658 Titre : Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan Type de document : Article/Communication Auteurs : Katsuto Shimizu, Auteur ; Tomohiro Nishizono, Auteur ; Fumiaki Kitahara, Auteur ; Keiko Fukumoto, Auteur ; Hideki Saito, Auteur Année de publication : 2022 Article en page(s) : n° 102658 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] estimation statistique [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] Japon [Termes IGN] Pinophyta [Termes IGN] volume en bois Résumé : (auteur) The accurate estimation of tree attributes is essential for sustainable forest management. Terrestrial Laser Scanning (TLS) is a viable remote sensing technology suitable for estimating under canopy structure. However, TLS measurements generally underestimate tree height in taller trees, which leads to the underestimation of other tree attributes (e.g., stem volume). The integration of information derived from TLS and Unmanned Aerial Vehicle (UAV) photogrammetry could potentially improve tree height estimation. This study investigated the applicability of integrating TLS and UAV photogrammetry to estimate individual tree attributes in managed coniferous forests of Japan. Diameter at breast height (DBH), tree height, and stem volume were estimated by (1) TLS data only, (2) integrating TLS and UAV data with TLS tree locations, and (3) integrating TLS and UAV data with treetop detections of the tree canopy. The TLS data only approach achieved high accuracy for DBH estimations with a root mean squared error (RMSE) of 2.36 cm (RMSE% 5.6%); however, tree height was greatly underestimated, with an RMSE of 8.87 m (28.9%) and a bias of −8.39 m. Integrating TLS and UAV photogrammetric data improved tree height estimation accuracy for both the TLS tree location (RMSE of 1.89 m and a bias of −0.46 m) and the treetop detection (RMSE of 1.77 m and a bias of 0.36 m) approaches. Integrating TLS and UAV photogrammetric data also improved the accuracy of the stem volume estimations with RMSEs of 0.21 m3 (10.8%) and 0.21 m3 (10.5%) for the TLS tree location and treetop detection approaches, respectively. Although the tree height of suppressed trees tended to be overestimated by TLS and UAV photogrammetric data integration, a good performance was obtained for dominant trees. The results of this study indicate that the integration of TLS and UAV photogrammetry is beneficial for the accurate estimation of tree attributes in coniferous forests. Numéro de notice : A2022-071 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102658 En ligne : https://doi.org/10.1016/j.jag.2021.102658 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99423 [article]

Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 184 (February 2022) . - pp 203 - 214 Titre : Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data Type de document : Article/Communication Auteurs : Tianyu Hu, Auteur ; Dengjie Wei, Auteur ; Yanjun Su, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 203 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre urbain [Termes IGN] canopée [Termes IGN] Chine [Termes IGN] couvert végétal [Termes IGN] distribution spatiale [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Green area index [Termes IGN] image panoramique [Termes IGN] semis de points [Termes IGN] système de numérisation mobile Résumé : (auteur) Street trees are important components of an urban green space and understanding and measuring their ecological and cultural services is crucial for assessing the quality of streets and managing urban environments. Currently, most studies mainly focus on evaluating the ecological services of street trees by measuring the amount of greenness, but how to evaluate their aesthetic functions through quantitative measurements of street trees remain unclear. To address this problem, we propose a method to assess the aesthetic functions of street trees by quantifying the shape of greenness inspired by assessments of skyline aesthetics. Using a state-of-the-art mobile mapping system, we collected downtown-wide lidar data and panoramic images in Jinzhou City, Hebei Province, China. We developed a method for extracting the canopy line from the mobile lidar data, and then identified two basic elements, peaks and gaps, from street canopy lines and extracted six indexes (i.e., richness of peaks, evenness of peaks, frequency of peaks, total length of gaps, evenness of gaps and frequency of gaps) to describe the fluctuations and continuities of street canopy lines. We analyzed the abundance and spatial distribution of these indexes together with survey responses on the streets’ aesthetics and found that most of them were significantly correlated with human perception of streets. Compared to indexes of amount of greenness (e.g., green volume and green view index), these shape indexes have stronger influences on the physical aesthetic beauty of street trees. These findings suggest that a comprehensive assessment of the aesthetic function of street trees should consider both shape and amount of greenness. This study provides a new perspective for the assessment of urban green spaces and can assist future urban greening planning and urban landscape management. Numéro de notice : A2022-105 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.002 Date de publication en ligne : 15/01/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99602 [article]

Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles / Nico Lang in Remote sensing of environment, vol 268 (January 2022)  

Public [article]  inRemote sensing of environment > vol 268 (January 2022) . - n* 112760 Titre : Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles Type de document : Article/Communication Auteurs : Nico Lang, Auteur ; Nicolai Kalischek, Auteur ; John Armston, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n* 112760 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage profond [Termes IGN] biomasse aérienne [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] estimation bayesienne [Termes IGN] forme d'onde [Termes IGN] Global Ecosystem Dynamics Investigation lidar [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] semis de points Résumé : (auteur) NASA's Global Ecosystem Dynamics Investigation (GEDI) is a key climate mission whose goal is to advance our understanding of the role of forests in the global carbon cycle. While GEDI is the first space-based LIDAR explicitly optimized to measure vertical forest structure predictive of aboveground biomass, the accurate interpretation of this vast amount of waveform data across the broad range of observational and environmental conditions is challenging. Here, we present a novel supervised machine learning approach to interpret GEDI waveforms and regress canopy top height globally. We propose a probabilistic deep learning approach based on an ensemble of deep convolutional neural networks (CNN) to avoid the explicit modelling of unknown effects, such as atmospheric noise. The model learns to extract robust features that generalize to unseen geographical regions and, in addition, yields reliable estimates of predictive uncertainty. Ultimately, the global canopy top height estimates produced by our model have an expected RMSE of 2.7 m with low bias. Numéro de notice : A2022-086 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112760 Date de publication en ligne : 03/11/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112760 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99495 [article]

Airborne LiDAR and high resolution multispectral data integration in Eucalyptus tree species mapping in an Australian farmscape / Niva Kiran Verma in Geocarto international, vol 37 n° 1 ([03/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 1 [03/01/2022] . - pp 70 - 90 Titre : Airborne LiDAR and high resolution multispectral data integration in Eucalyptus tree species mapping in an Australian farmscape Type de document : Article/Communication Auteurs : Niva Kiran Verma, Auteur ; David Lamb, Auteur ; Priyakant Sinha, Auteur Année de publication : 2022 Article en page(s) : pp 70 - 90 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Australie [Termes IGN] carte de la végétation [Termes IGN] dépérissement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Eucalyptus (genre) [Termes IGN] image à haute résolution [Termes IGN] image multibande [Termes IGN] précision de la classification [Termes IGN] segmentation d'image [Termes IGN] semis de points Résumé : (auteur) Rapid decline and death of rural Eucalypts trees of all ages and species have been reported in the farmscapes of regional Australia due to various environmental and farming management related factors. The identification of existing farm tree species is important for long term management strategies to provide ecosystem stability in the region. This study explored the feasibility of structural attributes of LiDAR and spectral and spatial characteristics of high resolution remote sensing data to identify and map Eucalyptus tree species. An object based image segmentation and rule-based classification algorithm were developed to delineate tree boundaries and species classification. The integration of two datasets improved the classification accuracy (65%) against their separate classification (52% and 41%, respectively). The identification of tree species will help in getting first-hand information on existing farm trees, which may be used in assessing tree condition in time series related to management practices and complex dieback problem. Numéro de notice : A2022-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1700555 Date de publication en ligne : 12/12/2019 En ligne : https://doi.org/10.1080/10106049.2019.1700555 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99412 [article]

A comparison of linear-mode and single-photon airborne LiDAR in species-specific forest inventories / Janne Raty in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 1 (January 2022) . - n° 4401514 Titre : A comparison of linear-mode and single-photon airborne LiDAR in species-specific forest inventories Type de document : Article/Communication Auteurs : Janne Raty, Auteur ; Petri Varvia, Auteur ; Lauri Korhonen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4401514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] altitude [Termes IGN] analyse comparative [Termes IGN] capteur linéaire [Termes IGN] carte de la végétation [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] instrumentation Leica [Termes IGN] instrumentation Riegl [Termes IGN] inventaire forestier étranger (données) [Termes IGN] photon [Termes IGN] Pinophyta [Termes IGN] semis de points [Termes IGN] signal laser Résumé : (auteur) Single-photon airborne light detection and ranging (LiDAR) systems provide high-density data from high flight altitudes. We compared single-photon and linear-mode airborne LiDAR for the prediction of species-specific volumes in boreal coniferous-dominated forests. The LiDAR data sets were acquired at different flight altitudes using Leica SPL100 (single-photon, 17 points ⋅ m−2 ), Riegl VQ-1560i (linear-mode, 11 points ⋅ m−2 ), and Leica ALS60 (linear-mode, 0.6 points ⋅ m−2 ) LiDAR systems. Volumes were predicted at the plot-level using Gaussian process regression with predictor variables extracted from the LiDAR data sets and aerial images. Our findings showed that the Leica SPL100 produced a greater mean root-mean-squared error (RMSE) value (41.7 m3 ⋅ ha −1 ) than the Leica ALS60 (39.3 m3 ⋅ ha −1 ) in the prediction of species-specific volumes. Correspondingly, the Riegl VQ-1560i (mean RMSE = 33.0 m3 ⋅ ha −1 ) outperformed both the Leica ALS60 and the Leica SPL100. We found that the cumulative distributions of the first echo heights >1.3 m were rather similar among the data sets, whereas the last echo distributions showed larger differences. We conclude that the Leica SPL100 data set is suitable for area-based LiDAR inventory by tree species although the prediction errors are greater than with data obtained using the modern linear-mode LiDAR, such as Riegl VQ-1560i. Numéro de notice : A2022-026 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1109/TGRS.2021.3060670 Date de publication en ligne : 04/03/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3060670 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99257 [article]

Utilisation 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)

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Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones / Lonesome Malambo in Remote sensing of environment, vol 266 (December 2021)  

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Application of a hand-held LiDAR scanner for the urban cadastral detail survey in digitized cadastral area of Taiwan urban city / Shih-Hong Chio in Remote sensing, vol 13 n° 24 (December-2 2021)  

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La 3D dans tous ses états [à Cergy-Pontoise] / Marielle Mayo in Géomètre, n° 2197 (décembre 2021)

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Atelier LiDAR mobile & aéroporté / Pierre Assali in XYZ, n° 169 (décembre 2021)

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Automatic registration of mobile mapping system Lidar points and panoramic-image sequences by relative orientation model / Ningning Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 12 (December 2021)  

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Digitizing for the future / Steve Snow in xyHt, vol 2021 n° 12 (December 2021)  

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Le Mont-Blanc mesuré au LiDAR héliporté / Mathieu Peyréga in XYZ, n° 169 (décembre 2021)

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La photogrammétrie appliquée au récolement des réseaux enterrés : retour d’expérience d’une méthode industrialisée / Jérôme Leroux in XYZ, n° 169 (décembre 2021)

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Point clouds for use in Building Information Models (BIM) / Robert Klinc in Geodetski vestnik, vol 65 n° 4 (December 2021 - February 2022)  

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