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Interurban visibility diagnosis from point clouds / Oscar Iglesias in European journal of remote sensing, vol 49 n° 1 (2016)
[article]
Titre : Interurban visibility diagnosis from point clouds Type de document : Article/Communication Auteurs : Oscar Iglesias, Auteur ; Lucia Diaz-Vilarino, Auteur ; Higinio González-Jorge, Auteur ; Henrique Lorenzo, Auteur Année de publication : 2016 Article en page(s) : pp 673 - 690 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] sécurité routière
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] télémétrie laser terrestre
[Termes IGN] visibilitéRésumé : (auteur) We present an approach for automatic visibility analysis in interurban roads from point clouds. The methodology is based on a ray-tracing algorithm followed by an occlusion detection to identify potential obstacles between the driver and the theoretical position of pedestrians and cyclists. As a result, the area of visibility from each driver position is obtained. The method compares the performance and suitability of point clouds acquired from both Airborne and Mobile Laser Scanning. The methodology is tested in six real case studies. In most cases, results obtained from MLS are more accurate since the point clouds are acquired from a perspective similar to driver and they have higher resolution. Numéro de notice : A2016-828 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164935 En ligne : http://dx.doi.org/10.5721/EuJRS20164935 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82708
in European journal of remote sensing > vol 49 n° 1 (2016) . - pp 673 - 690[article]Relative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation / Alyssa Endres in European journal of remote sensing, vol 49 n° 1 (2016)
[article]
Titre : Relative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation Type de document : Article/Communication Auteurs : Alyssa Endres, Auteur ; Giorgos Mountrakis, Auteur ; Huiran Jin, Auteur ; Wei Zhuang, Auteur ; Ioannis Manakos, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 795 - 807 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] biomasse aérienne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] feuillu
[Termes IGN] fusion de données
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image LandsatRésumé : (auteur) Aboveground forest biomass estimation is an integral component for climate change, carbon stocks assessment, biodiversity and forest health. LiDAR (Light Detection And Ranging), specifically NASA’s Laser Vegetation Imaging Sensor (LVIS), PALSAR (Phased Array type L-band Synthetic Aperture Radar), and Landsat data have been previously used in biomass estimation with promising results when used individually. In this manuscript, all three products are jointly utilized for the first time to assess their importance for deciduous biomass estimation. Results indicate that LVIS inputs are ranked as most important followed by PALSAR inputs. Particularly for PALSAR, scenes acquired in May and August were ranked higher compared to other months. Numéro de notice : A2016-827 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164942 En ligne : http://dx.doi.org/10.5721/EuJRS20164942 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82707
in European journal of remote sensing > vol 49 n° 1 (2016) . - pp 795 - 807[article]A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data / Hamid Hamraz in International journal of applied Earth observation and geoinformation, vol 52 (October 2016)
[article]
Titre : A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data Type de document : Article/Communication Auteurs : Hamid Hamraz, Auteur ; Marco A. Contreras, Auteur ; Jun Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 532 - 541 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Kentucky (Etats-Unis)
[Termes IGN] pente
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) This paper presents a non-parametric approach for segmenting trees from airborne LiDAR data in deciduous forests. Based on the LiDAR point cloud, the approach collects crown information such as steepness and height on-the-fly to delineate crown boundaries, and most importantly, does not require a priori assumptions of crown shape and size. The approach segments trees iteratively starting from the tallest within a given area to the smallest until all trees have been segmented. To evaluate its performance, the approach was applied to the University of Kentucky Robinson Forest, a deciduous closed-canopy forest with complex terrain and vegetation conditions. The approach identified 94% of dominant and co-dominant trees with a false detection rate of 13%. About 62% of intermediate, overtopped, and dead trees were also detected with a false detection rate of 15%. The overall segmentation accuracy was 77%. Correlations of the segmentation scores of the proposed approach with local terrain and stand metrics was not significant, which is likely an indication of the robustness of the approach as results are not sensitive to the differences in terrain and stand structures. Numéro de notice : A2016-705 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2016.07.006 En ligne : http://dx.doi.org/10.1016/j.jag.2016.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82075
in International journal of applied Earth observation and geoinformation > vol 52 (October 2016) . - pp 532 - 541[article]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]An individual tree-based automated registration of aerial images to LiDAR Data in a forested area / Jun-Hak Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)
[article]
Titre : An individual tree-based automated registration of aerial images to LiDAR Data in a forested area Type de document : Article/Communication Auteurs : Jun-Hak Lee, Auteur ; Gregory S. Biging, Auteur Année de publication : 2016 Article en page(s) : pp 699 - 710 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre (flore)
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] écosystème forestier
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] point d'appui
[Termes IGN] superposition d'imagesRésumé : (Auteur) In this paper, we demonstrate an approach to align aerial images to airborne lidar data by using common object features (tree tops) from both data sets under the condition that conventional correlation-based approaches are challenging due to the fact that the spatial pattern of pixel gray-scale values in aerial images hardly exist in lidar data. We extracted tree tops by using an image processing technique called extended-maxima transformation from both aerial images and lidar data. Our approach was tested at the Angelo Coast Range Reserve on the South Fork Eel River forests in Mendocino County, California. Although the aerial images were acquired simultaneously with the lidar data, the images had only approximate exposure point locations and average flight elevation information, which mimicked the condition of limited information availability about the aerial images. Our results showed that this approach enabled us to align aerial images to airborne lidar data at the single-tree level with reasonable accuracy. With a local transformation model (piecewise linear model), the RMSE and the median absolute deviation (MAD) of the registration were 9.2 pixels (2.3 meters) and 6.8 pixels (1.41 meters), respectively. We expect our approach to be applicable to fine scale change detection for forest ecosystems and may serve to extract detailed forest biophysical parameters. Numéro de notice : A2016-740 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.9.699 En ligne : https://doi.org/10.14358/PERS.82.9.699 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82275
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 9 (September 2016) . - pp 699 - 710[article]Development of a mixed pixel filter for improved dimension estimation using AMCW laser scanner / Qiang Wang in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkEstimating the solar transmittance of urban trees using airborne LiDAR and radiative transfer simulation / Haruki Oshio in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkInternational benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning / Yunsheng Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkLocal-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data / Radosław Malinowski in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkMonitoring 3D vibrations in structures using high-resolution blurred imagery / David M.J. McCarhy in Photogrammetric record, vol 31 n° 155 (September - November 2016)PermalinkReconstruction en 3D des bâtiments à partir des données Lidar / M. A. Missomi in Géomatique expert, n° 112 (septembre - octobre 2016)PermalinkSlicing method for curved façade and window extraction from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkA local structure and direction-aware optimization approach for three-dimensional tree modeling / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkUnsupervised 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)PermalinkImproved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas / Xiaoqian Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)Permalink