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Lidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)
[article]
Titre : Lidar detection of individual tree size in tropical forests Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Victoria Meyer, Auteur Année de publication : 2016 Projets : 1-Pas de projet / Article en page(s) : pp 318 - 333 Note générale : Bibliographie
António Ferraz's research was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, administrated by Oak Ridge Associated Universities under contract with NASA(grant number NNH15CO48B).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Panama
[Termes IGN] semis de points
[Termes IGN] télédétection aérienneRésumé : (Auteur) Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1ha, 2.25 ha, 4ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from16.9% at 1ha for the worst model to 5.0% at 6.25ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies. Numéro de notice : A2016--103 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.05.028 Date de publication en ligne : 21/06/2016 En ligne : http://doi.org/10.1016/j.rse.2016.05.028 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84669
in Remote sensing of environment > vol 183 (15 September 2016) . - pp 318 - 333[article]CHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations / Karolina D. Fieber in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
[article]
Titre : CHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations Type de document : Article/Communication Auteurs : Karolina D. Fieber, Auteur ; Ian J. Davenport, Auteur ; James M. Ferryman, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 5071 - 5080 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] forme d'onde pleine
[Termes IGN] hauteur des arbres
[Termes IGN] Leaf Area Index
[Termes IGN] logiciel libre
[Termes IGN] vergerRésumé : (Auteur) This paper presents an open-source canopy height profile (CHP) toolkit designed for processing small-footprint full-waveform LiDAR data to obtain the estimates of effective leaf area index (LAIe) and CHPs. The use of the toolkit is presented with a case study of LAIe estimation in discontinuous-canopy fruit plantations. The experiments are carried out in two study areas, namely, orange and almond plantations, with different percentages of canopy cover (48% and 40%, respectively). For comparison, two commonly used discrete-point LAIe estimation methods are also tested. The LiDAR LAIe values are first computed for each of the sites and each method as a whole, providing “apparent” site-level LAIe, which disregards the discontinuity of the plantations' canopies. Since the toolkit allows for the calculation of the study area LAIe at different spatial scales, between-tree-level clumping can be easily accounted for and is then used to illustrate the impact of the discontinuity of canopy cover on LAIe retrieval. The LiDAR LAIe estimates are therefore computed at smaller scales as a mean of LAIe in various grid-cell sizes, providing estimates of “actual” site-level LAIe. Subsequently, the LiDAR LAIe results are compared with theoretical models of “apparent” LAIe versus “actual” LAIe, based on known percent canopy cover in each site. The comparison of those models to LiDAR LAIe derived from the smallest grid-cell sizes against the estimates of LAIe for the whole site has shown that the LAIe estimates obtained from the CHP toolkit provided values that are closest to those of theoretical models. Numéro de notice : A2016-894 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2550623 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2550623 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83074
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 9 (September 2016) . - pp 5071 - 5080[article]Propagating uncertainty through individual tree volume model predictions to large-area volume estimates / Ronald E. McRoberts in Annals of Forest Science, vol 73 n° 3 (September 2016)
[article]
Titre : Propagating uncertainty through individual tree volume model predictions to large-area volume estimates Type de document : Article/Communication Auteurs : Ronald E. McRoberts, Auteur ; James A. Westfall, Auteur Année de publication : 2016 Article en page(s) : pp 625 – 633 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] diamètre des arbres
[Termes IGN] hauteur des arbres
[Termes IGN] incertitude des données
[Termes IGN] modèle de simulation
[Termes IGN] prédiction
[Termes IGN] propagation d'erreur
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : The effects on large-area volume estimates of uncertainty in individual tree volume model predictions were negligible when using simple random sampling estimators for large-area estimation, but non-negligible when using stratified estimators which reduced the effects of sampling variability.
Context : Forest inventory estimates of tree volume for large areas are typically calculated by adding model predictions of volumes for individual trees at the plot level and calculating the per unit area mean over plots. The uncertainty in the model predictions is generally ignored with the result that the precision of the large-area volume estimate is optimistic.
Aims : The primary objective was to estimate the effects on large-area volume estimates of volume model prediction uncertainty due to diameter and height measurement error, parameter uncertainty, and model residual variance.
Methods : Monte Carlo simulation approaches were used because of the complexities associated with multiple sources of uncertainty, the non-linear nature of the models, and heteroskedasticity.
Results : The effects of model prediction uncertainty on large-area volume estimates of growing stock volume were negligible when using simple random sampling estimators. However, with stratified estimators that reduce the effects of sampling variability, the effects of model prediction uncertainty were not necessarily negligible. The adverse effects of parameter uncertainty and residual variance were greater than the effects of diameter and height measurement errors.
Conclusion : The uncertainty of large-area volume estimates that do not account for model prediction uncertainty should be regarded with caution.Numéro de notice : A2016-711 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-015-0473-x Date de publication en ligne : 22/04/2015 En ligne : https://doi.org/10.1007/s13595-015-0473-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82089
in Annals of Forest Science > vol 73 n° 3 (September 2016) . - pp 625 – 633[article]Airborne lidar estimation of aboveground forest biomass in the absence of field inventory / António Ferraz in Remote sensing, vol 8 n° 8 (August 2016)
[article]
Titre : Airborne lidar estimation of aboveground forest biomass in the absence of field inventory Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Stéphane Jacquemoud, Auteur ; Gil Rito-Gonçalves , Auteur ; Carlos Alberto Silva, Auteur ; Paola Soares, Auteur ; Margarida Tomé, Auteur ; Luisa Pereira, Auteur Année de publication : 2016 Projets : 3-projet - voir note / Article en page(s) : pp 1 - 18 Note générale : Bibliographie
This work was supported in part by the Portuguese Foundation for Science and Technology under Grant PTDC/AGR-CFL/72380/2006, co-financed by the European Fund of Regional Development (FEDER) through COMPETE—Operational Factors of Competitiveness Program (POFC) and the Grant Pest-OE/EEI/UI308/2014Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] analyse de groupement
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification automatique d'objets
[Termes IGN] couvert végétal
[Termes IGN] dendrométrie
[Termes IGN] données lidar
[Termes IGN] extraction d'arbres
[Termes IGN] fiabilité des données
[Termes IGN] houppier
[Termes IGN] Portugal
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) The scientific community involved in the UN-REDD program is still reporting large uncertainties about the amount and spatial variability of CO2 stored in forests. The main limitation has been the lack of field samplings over space and time needed to calibrate and convert remote sensing measurements into aboveground biomass (AGB). As an alternative to costly field inventories, we examine the reliability of state-of-the-art lidar methods to provide direct retrieval of many forest metrics that are commonly collected through field sampling techniques (e.g., tree density, individual tree height, crown cover). AGB is estimated using existing allometric equations that are fed by lidar-derived metrics at either the individual tree- or forest layer-level (for the overstory or underneath layers, respectively). Results over 40 plots of a multilayered forest located in northwest Portugal show that the lidar method provides AGB estimates with a relatively small random error (RMSE = of 17.1%) and bias (of 4.6%). It provides local AGB baselines that meet the requirements in terms of accuracy to calibrate satellite remote sensing measurements (e.g., the upcoming lidar GEDI (Global Ecosystem Dynamics Investigation), and the Synthetic Aperture Radar (SAR) missions NISAR (National Aeronautics and Space Administration and Indian Space Research Organization SAR) and BIOMASS from the European Space Agency, ESA) for AGB mapping purposes. The development of similar techniques over a variety of forest types would be a significant improvement in quantifying CO2 stocks and changes to comply with the UN-REDD policies. Numéro de notice : A2016--104 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs8080653 Date de publication en ligne : 12/08/2016 En ligne : https://doi.org/10.3390/rs8080653 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84675
in Remote sensing > vol 8 n° 8 (August 2016) . - pp 1 - 18[article]Documents numériques
en open access
A2016--104_Airborne_lidar_estimation_of_aboveground_forest_biomassAdobe Acrobat PDF Basal area and diameter distribution estimation using stereoscopic hemispherical images / Mariola Sánchez-González in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)
[article]
Titre : Basal area and diameter distribution estimation using stereoscopic hemispherical images Type de document : Article/Communication Auteurs : Mariola Sánchez-González, Auteur ; Miguel Cabrera, Auteur ; Pedro Javier Herrera, Auteur Année de publication : 2016 Article en page(s) : pp 605 - 616 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'images
[Termes IGN] courbe de Pearson
[Termes IGN] diamètre des arbres
[Termes IGN] image hémisphérique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle stéréoscopique
[Termes IGN] placette d'échantillonnage
[Termes IGN] surface terrière
[Termes IGN] tronc
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) In recent years, proximal sensing data has increasingly been used to optimize forest inventories. In this paper, we present a forest inventory methodology based on stereoscopic hemispherical images. An automated pixel-based approach and a user-guided “region growing” approach have been developed for image matching. To estimate the basal area, number of trees and mean diameter, the sampling probability is determined for each tree. The accuracy and precision of the estimates derived from stereoscopic hemispherical images was analyzed for a set of National Forest Inventory plots. The results revealed that tree matching depends on the species, the distance to the target tree and the diameter. The Pearson correlation coefficient was 0.86 for the mean diameter and 0.89 for the basal area, whereas for the number of trees per hectare it was 0.59. The proposed methods may be used in large scale forest inventories as a cost-efficient way of obtaining data on diameter distribution and basal area from field surveys following a two-stage scheme combined with remote sensing techniques. Numéro de notice : A2016-607 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.8.605 En ligne : http://dx.doi.org/10.14358/PERS.82.8.605 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81805
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 8 (August 2016) . - pp 605 - 616[article]Unsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning / Jari Vauhkonen in Forestry, an international journal of forest research, vol 89 n° 4 (August 2016)PermalinkLidar imagery and InSAR for digital forestry / Benoît Saint-Onge in GIM international, vol 30 n° 7 (July 2016)PermalinkNationwide airborne laser scanning based models for volume, biomass and dominant height in Finland / Eetu Kotivuori in Silva fennica, vol 50 n° 4 (2016)PermalinkDeveloping a dynamic growth model for maritime pine in Asturias (NW Spain): comparison with nearby regions / Manuel Arias-Rodil in Annals of Forest Science, vol 73 n° 2 (June 2016)PermalinkEstimations dendrométriques pour l’aménagement forestier à l’aide de LiDAR aéroporté : premier démonstrateur en forêts littorales dunaires / Alain Munoz in Rendez-vous techniques, n° 50 (Hiver 2016)PermalinkExpérience pratique de la réalisation du projet démonstrateur « LiDAR forestier » / Didier Canteloup in Rendez-vous techniques, n° 50 (Hiver 2016)PermalinkRelationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkUsing classification trees to predict forest structure types from LiDAR data / Chiara Torresan in Annals of forest research, vol 59 n° 2 (July - December 2016)PermalinkWavelet analysis of low-frequency variability in oak tree-ring chronologies from east Central Europe / Asok K. Sen in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkICESat/GLAS canopy height sensitivity inferred from Airborne Lidar / Craig Mahoney in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)Permalink