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Sensitivity 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)  

Public [article]  inRemote sensing of environment > vol 257 (May 2021) . - n° 112354 Titre : Sensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment Type de document : Article/Communication Auteurs : Maxime Soma, Auteur ; François Pimont, Auteur ; Jean-Luc Dupuy, Auteur Année de publication : 2021 Article en page(s) : n° 112354 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de sensibilité [Termes IGN] densité du feuillage [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] échantillonnage [Termes IGN] Leaf Area Index [Termes IGN] Leaf Mass per Area [Termes IGN] semis de points [Termes IGN] structure de la végétation [Termes IGN] voxel Résumé : (auteur) The need for fine scale description of vegetation structure is increasing as Leaf Area Density (LAD, m2/m3) becomes a critical parameter to understand ecosystem functioning and energy and mass fluxes in heterogeneous ecosystems. Terrestrial Laser Scanning (TLS) has shown great potential for retrieving the foliage area at stand, plant or voxel scales. Several sources of measurement errors have been identified and corrected over the past years. However, measurements remain sensitive to several factors, including, 1) voxel size and vegetation structure within voxels, 2) heterogeneity in sampling from TLS instrument (occlusion and shooting pattern), the consequences of which have been seldom analyzed at the scale of forest plots. In the present paper, we aimed at disentangling biases and errors in plot-scale measurements of LAD with TLS in a simulated vegetation scene. Two negative biases were formerly attributed to (i) the unsampled voxels and to (ii) the subgrid vegetation heterogeneity (i.e. clumping effect), and then quantified, thanks to a the simulation experiment providing known LAD references at voxel scale, vegetation manipulations and unbiased point estimators. We used confidence intervals to evaluate voxel-scale measurement accuracy. Numéro de notice : A2021-278 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112354 Date de publication en ligne : 18/02/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112354 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97371 [article]

An 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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 3547 - 3566 Titre : An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects Type de document : Article/Communication Auteurs : Linyuan Li, Auteur ; Xihan Mu, Auteur ; Maxime Soma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3547 - 3566 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] détection de partie cachée [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données de terrain [Termes IGN] données lidar [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] itération [Termes IGN] semis de points Résumé : (auteur) Occlusion effect, an inherent problem of terrestrial laser scanning (TLS) measurements, limits the potential of TLS data in tree attribute estimation. Multiple scans seek to mitigate this effect to provide enhanced scan completeness. However, the numbers and locations of the scans (i.e., the scan design) are usually determined via a subjective assessment of the tree density, spatial patterns of trees, and attributes to be derived. These could cause suboptimal scan completeness and limit tree attribute estimation. This study proposed an iterative-mode scan design to minimize the occlusion effect. First, we introduced a PoTo index based on visibility analysis to evaluate how many trees can be scanned from a location and to select effective candidates for the optimal TLS location. Second, we introduced a cumulative degree of ring closure (CDRC) to quantify the scan completeness for each candidate and determine the optimal TLS location. The TLS data sets of virtual forests with field-measured and synthetic plot parameter settings were simulated according to iterative- and regular-mode designs by using a Heidelberg light detection and ranging (LiDAR) Operations Simulator (HELIOS). The results demonstrated that an iterative-mode design can improve the scan completeness of trees compared to the regular-mode design. The tree attribute (diameter at breast height (DBH), tree height, stem curve, and crown volume) estimates of the iterative-mode design were less erroneous than those of the regular-mode design (e.g., the root-mean-square error (RMSE) could decrease the stem curve estimation by 38% and the crown volume estimation by 15%). This study suggests that the iterative-mode design can obtain an improved quality of the TLS data, especially for dense stands. Numéro de notice : A2021-288 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3018643 Date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3018643 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97397 [article]

Improving GEDI footprint geolocation using a high resolution digital terrain model / Anouk Schleich (2021)  

Public Titre : Improving GEDI footprint geolocation using a high resolution digital terrain model Type de document : Article/Communication Auteurs : Anouk Schleich, Auteur ; Maxime Soma, Auteur ; Sylvie Durrieu, Auteur ; Cédric Vega , Auteur ; Jean-Pierre Renaud , Auteur ; Olivier Bouriaud , Auteur Editeur : Vienne [Autriche] : Technische Universität Wien Année de publication : 2021 Collection : Geowissenschaftliche Mitteilungen, ISSN 1811-8380 num. 104 Projets : TOSCA SLIM / Conférence : SilviLaser 2021, 17th conference on Lidar Applications for Assessing and Managing Forest Ecosystems 28/09/2021 30/09/2021 Vienne + online Autriche open access proceedings Importance : pp 179 - 181 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] fauchée [Termes IGN] géoréférencement [Termes IGN] Global Ecosystem Dynamics Investigation lidar [Termes IGN] modèle numérique de terrain Résumé : (auteur) [introduction] In 2018, NASA launched the Global Ecosystem Dynamics Investigation (GEDI) mission, a high resolution lidar system installed onboard the International Space Station (ISS). It is producing high quality 3D observations of the Earth surface structure, which are highly relevant to study forest ecosystems at a global scale (Qi et al. 2019). GEDI data is composed of 25 m diameter circular footprints for which the waveform of the received energy intensity returned by the ground is recorded. Each GEDI footprint is georeferenced and its positioning accuracy (for version 1 releases) is estimated at 15-20 m in planimetry with a systematic component of 8-10 m and a noise of the order of 8 m (1). A final horizontal geolocation accuracy of 8 m is expected after further processing in the final version (Dubayah et al. 2020). Compared to most other spatial satellites the ISS is much closer to earth, causing more variations in its orientation and altitude. Therefore, geolocating data acquired by ISS sensors is more diffucult than geolocating data aquired by satellites (Dou et al. 2014). An improved geolocation of GEDI data is mandatory to evaluate their quality, by comparison with other earth observation data or field measurements, and to further facilitate their integration in ecosystem monitoring approaches. We propose a method to improve the georeferencing of GEDI footprints using a precise Digital Terrain Model (DTM). Numéro de notice : C2021-053 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.34726/wim.1973 Date de publication en ligne : 01/12/2021 En ligne : https://doi.org/10.34726/wim.1973 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99223