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Auteur Arko Lucieer |
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Footprint determination of a spectroradiometer mounted on an unmanned aircraft system / Deepak Gautam in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
[article]
Titre : Footprint determination of a spectroradiometer mounted on an unmanned aircraft system Type de document : Article/Communication Auteurs : Deepak Gautam, Auteur ; Arko Lucieer, Auteur ; Juliane Bendig, Auteur Année de publication : 2020 Article en page(s) : pp 3085 - 3096 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] canopée
[Termes IGN] capteur aérien
[Termes IGN] carte de la végétation
[Termes IGN] chlorophylle
[Termes IGN] classification pixellaire
[Termes IGN] drone
[Termes IGN] échantillonnage
[Termes IGN] empreinte
[Termes IGN] fluorescence
[Termes IGN] géoréférencement
[Termes IGN] photosynthèse
[Termes IGN] point d'appui
[Termes IGN] réflectance spectrale
[Termes IGN] signature spectrale
[Termes IGN] spectroradiomètreRésumé : (auteur) Unmanned aircraft system (UAS)-mounted spectroradiometers offer a new capability to measure spectral reflectance and solar-induced chlorophyll fluorescence at detailed canopy scales. This capability offers potential for upscaling and comparison with airborne and space-borne observations [e.g., the upcoming European Space Agency (ESA) Fluorescence Explorer (FLEX) satellite mission]. In this respect, the accurate spatial characterization and georeferencing of the UAS acquisition footprints are essential to unravel the origin and spatial variability of optical signals acquired within the extent of airborne/satellite pixels. In this article, we present and validate a novel algorithm to georeference the footprint extent of a nonimaging spectroradiometer mounted on a multirotor UAS platform. We used information about the spectroradiometer position and orientation during flight and about topography of observed terrain to calculate the footprint geolocation. In a recursive process, the field of view (FOV) of the spectroradiometer projected on the ground. Multiple FOV ground projections retrieved during a spectroradiometer reading (i.e., a single integration time) were aggregated to calculate the footprint extent. The spatial accuracy of the footprint geolocation was validated by applying the georeferencing algorithm on checkpoint pixels of image acquired with a comounted digital camera. Geolocations of the checkpoint pixels, which served as a proxy for the spectroradiometer footprint, were successfully compared with surveyed ground checkpoints. Finally, the spectral and radiometric quality of UAS-acquired reflectance signatures was compared with ground-measured reflectance of four natural targets (three different types of grass and a bare soil), and a strong agreement was observed. Numéro de notice : A2020-233 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947703 Date de publication en ligne : 06/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947703 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94978
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 3085 - 3096[article]Evaluating tree detection and segmentation routines on very high resolution UAV LiDAR data / Luke Wallace in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)
[article]
Titre : Evaluating tree detection and segmentation routines on very high resolution UAV LiDAR data Type de document : Article/Communication Auteurs : Luke Wallace, Auteur ; Arko Lucieer, Auteur ; Christopher S. Watson, Auteur Année de publication : 2014 Article en page(s) : pp 7619 - 7628 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre (flore)
[Termes IGN] canopée
[Termes IGN] contour
[Termes IGN] détection de cible
[Termes IGN] données lidar
[Termes IGN] drone
[Termes IGN] Eucalyptus globulus
[Termes IGN] hauteur des arbres
[Termes IGN] image à très haute résolution
[Termes IGN] implémentation (informatique)
[Termes IGN] prise de vue aérienne
[Termes IGN] semis de pointsRésumé : (Auteur) Light detection and Ranging (LiDAR) is becoming an increasingly used tool to support decision-making processes within forest operations. Area-based methods that derive information on the condition of a forest based on the distribution of points within the canopy have been proven to produce reliable and consistent results. Individual tree-based methods, however, are not yet used operationally in the industry. This is due to problems in detecting and delineating individual trees under varying forest conditions resulting in an underestimation of the stem count and biases toward larger trees. The aim of this paper is to use high-resolution LiDAR data captured from a small multirotor unmanned aerial vehicle platform to determine the influence of the detection algorithm and point density on the accuracy of tree detection and delineation. The study was conducted in a four-year-old Eucalyptus globulus stand representing an important stage of growth for forest management decision-making process. Five different tree detection routines were implemented, which delineate trees directly from the point cloud, voxel space, and the canopy height model (CHM). The results suggest that both algorithm and point density are important considerations in the accuracy of the detection and delineation of individual trees. The best performing method that utilized both the CHM and the original point cloud was able to correctly detect 98% of the trees in the study area. Increases in point density (from 5 to 50 points/m2) lead to significant improvements (of up to 8%) in the rate of omission for algorithms that made use of the high density of the data. Numéro de notice : A2014-640 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2315649 En ligne : https://doi.org/10.1109/TGRS.2014.2315649 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75077
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 12 (December 2014) . - pp 7619 - 7628[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014121 RAB Revue Centre de documentation En réserve L003 Disponible An assessment of the repeatability of automatic forest inventory metrics derived from UAV-borne laser scanning data / Luke Wallace in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)
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Titre : An assessment of the repeatability of automatic forest inventory metrics derived from UAV-borne laser scanning data Type de document : Article/Communication Auteurs : Luke Wallace, Auteur ; Robert Musk, Auteur ; Arko Lucieer, Auteur Année de publication : 2014 Article en page(s) : pp 7160 - 7169 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de cible
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] semis de pointsRésumé : (Auteur) We assessed the reproducibility of forest inventory metrics derived from an unmanned aerial vehicle (UAV) laser scanning (UAVLS) system. A total of 82 merged point clouds were captured over six 500-m2 plots within a Eucalyptus globulus plantation forest in Tasmania, Australia. Terrain and understory height, together with plot- and tree-level metrics, were extracted from the UAVLS point clouds using automated methods and compared across the multiple point clouds. The results show that measurements of terrain and understory height and plot-level metrics can be reproduced with adequate repeatability for change detection purposes. At the tree level, the high-density data collected by the UAV provided estimates of tree location (mean deviation (MD) of less than 0.48 m) and tree height (MD of 0.35 m) with high precision. This precision is comparable to that of ground-based field measurement techniques. The estimates of crown area and crown volume were found to be dependent on the segmentation routine and, as such, were measured with lower repeatability. The precision of the metrics found within this paper demonstrates the applicability of UAVs as a platform for performing sample-based forest inventories. Numéro de notice : A2014-539 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2308208 En ligne : https://doi.org/10.1109/TGRS.2014.2308208 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74156
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 11 tome 1 (November 2014) . - pp 7160 - 7169[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014111A RAB Revue Centre de documentation En réserve L003 Disponible Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty / Arko Lucieer in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
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Titre : Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty Type de document : Article/Communication Auteurs : Arko Lucieer, Auteur ; Alfred Stein, Auteur ; Peter F. Fisher, Auteur Année de publication : 2005 Article en page(s) : pp 2917 - 2936 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] extraction automatique
[Termes IGN] image CASI
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] niveau de gris (image)
[Termes IGN] objet géographique
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (Auteur) In this study, a segmentation procedure is proposed, based on grey-level and multivariate texture to extract spatial objects from an image scene. Object uncertainty was quantified to identify transitions zones of objects with indeterminate boundaries. The Local Binary Pattern (LBP) operator, modelling texture, was integrated into a hierarchical splitting segmentation to identifiy homogeneous texture regions in an image. We proposed a multivariate extension of the standard univariate LBP operator to describe colour texture. The paper is illustrated with two case studies. The first considers an image with a composite of texture regions. The two LBP operators provided good segmentation results on both grey-scale and colour textures, depicted by accuracy values of 96% and 98% respectively. The second case study involved segmentation of coastal land cover objects from a multispectral Compact Airborne Spectral Imager (CASI) image, of a coastal area in the UK. Segmentation based on the univariate LBP measure provided unsatisfactory segmentation results from a single CASI band (70% accuracy). A multivariate LBP-based segmentation of three CASI bands improved segmentation results considerably (77% accuracy). Uncertainty values for object building blocks provided valuable information for identification of object transition zones. We conclude that the multivariate LBP texture model in combinaison with a hierarchical splitting segmentation framework is suitable for identifying objects and for quantifying their uncertainty. Numéro de notice : A2005-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500057723 En ligne : https://doi.org/10.1080/01431160500057723 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27430
in International Journal of Remote Sensing IJRS > vol 26 n° 14 (July 2005) . - pp 2917 - 2936[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05141 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Interactive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty / Arko Lucieer in International journal of geographical information science IJGIS, vol 18 n° 5 (august 2004)
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Titre : Interactive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty Type de document : Article/Communication Auteurs : Arko Lucieer, Auteur ; Menno-Jan Kraak, Auteur Année de publication : 2004 Article en page(s) : pp 491 - 512 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification floue
[Termes IGN] image Landsat-ETM+
[Termes IGN] incertitude des données
[Termes IGN] interactivité
[Termes IGN] visualisationRésumé : (Auteur) In this study, we propose, describe, and demonstrate a new geovisualization tool to demonstrate the use of exploratory and interactive visualization techniques for a visual fuzzy classification of remotely sensed imagery. The proposed tool uses dynamically linked views, consisting of an image display, a parallel coordinate plot, a 3D feature space plot, and a classified map with an uncertainty map. It allows a geoscientist to interact with the parameters of a fuzzy classification algorithm by visually adjusting fuzzy membership functions and fuzzy transition zones of land-cover classes. The purpose of this tool is to improve insight into fuzzy classification of remotely sensed imagery and related uncertainty. We tested our tool with a visual fuzzy land-cover classification of a Landsat 7 ETM + image of an area ln southern France characterized by objects with indeterminate boundaries. Good results were obtained with the visual classifier. Additionally, a focus-group user test of the tool showed that insight into a fuzzy classification algorithm and classification uncertainty improved considerably. Numéro de notice : A2004-284 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810410001658094 En ligne : https://doi.org/10.1080/13658810410001658094 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26811
in International journal of geographical information science IJGIS > vol 18 n° 5 (august 2004) . - pp 491 - 512[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-04051 RAB Revue Centre de documentation En réserve L003 Disponible