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An application-oriented automated approach for co-registration of forest inventory and airborne laser scanning data / W. Dorigo in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 31 n° 5 (March 2010) . - pp 1133 - 1153 Titre : An application-oriented automated approach for co-registration of forest inventory and airborne laser scanning data Type de document : Article/Communication Auteurs : W. Dorigo, Auteur ; Markus Hollaus, Auteur ; W. Wagner, Auteur ; Klemens Schadauer, Auteur Année de publication : 2010 Conférence : Silvilaser 2008, 8th international conference on Lidar applications in forest assessment and inventory 17/09/2008 19/09/2008 Edimbourg Royaume-Uni Proceedings Taylor&Francis Article en page(s) : pp 1133 - 1153 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Autriche [Termes IGN] canopée [Termes IGN] données laser [Termes IGN] données localisées 3D [Termes IGN] feuillu [Termes IGN] hauteur des arbres [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lasergrammétrie [Termes IGN] télémétrie laser aéroporté Résumé : (Auteur) Airborne laser scanning (ALS) data can be used for downscaling point-based forest inventory (FI) measurements to obtain spatially distributed estimates of forest parameters at a more detailed, local scale. Such downscaling algorithms usually consist of a direct coupling between selected FI parameters and ALS data collected at the field sampling locations. Thus, precise co-registration between FI and ALS data is an essential preprocessing step to obtain accurate predictive relationships. This paper presents a new, automated co-registration approach that searches iteratively for the best match between an ALS-based canopy height model and the tree positions and heights measured during the FI. While the basic principle of the algorithm applies to various types of FI sampling configurations, the co-registration approach was developed specifically to take into account the tree selection criterion posed by angle count sampling. The angle count sampling method only includes trees that at a given distance from the sample plot centre have a minimum required diameter at breast height (DBH). This tree selection criterion leads to maximum plot radii and number of inventoried trees that strongly vary from sample plot to sample plot. In the automated co-registration procedure, several criteria (e.g. the occurrence of more than one spatial cluster of minimum residuals and a predominance of deciduous trees in a sample plot) were used to detect possible uncertain solutions and to reduce post-processing efforts by an image operator. Model calibration and validation were based on national forest inventory (NFI) and ALS data from the Austrian federal state of Vorarlberg. Transferability and robustness of the approach was verified using an independent local FI. The results show that 68% of the NFI sample plots and 74% of the local FI plots could be automatically co-registered to a location at a distance of less than 5.0 m from the reference location. The maximum difference of 5.0 m used for marking a solution as correct was based on the relatively small influence that deviations of up to this value have on ALS-based predictions of biophysical forest variables at a stand level. The quality flagging criteria adopted were very successful in identifying uncertain solutions; only one out of 153 co-registered sample plots with a deviation from the reference data set greater than 5.0 m was not identified as uncertain. Applying the automatically co-registered sample plots in calibration of a growing stock model provided estimates that were clearly superior to those obtained with the original plot positions and even slightly outperformed those based on manual co-registration. As the algorithm developed will be part of an operational processing chain for Austrian NFI data, it has a high practical relevance. Copyright Taylor & Francis Numéro de notice : A2010-250 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160903380581 En ligne : https://doi.org/10.1080/01431160903380581 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30444 [article]

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080-2010031	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt

Lidar mapping of canopy gaps in continuous cover forests : a comparison of canopy height model and point cloud based techniques / Rachel Gaulton in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 31 n° 5 (March 2010) . - pp 1193 - 1211 Titre : Lidar mapping of canopy gaps in continuous cover forests : a comparison of canopy height model and point cloud based techniques Type de document : Article/Communication Auteurs : Rachel Gaulton, Auteur ; T.J. Malthus, Auteur Année de publication : 2010 Conférence : Silvilaser 2008, 8th international conference on Lidar applications in forest assessment and inventory 17/09/2008 19/09/2008 Edimbourg Royaume-Uni Proceedings Taylor&Francis Article en page(s) : pp 1193 - 1211 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] couvert forestier [Termes IGN] données lidar [Termes IGN] hauteur des arbres [Termes IGN] semis de points [Termes IGN] surveillance forestière [Termes IGN] système d'information géographique Résumé : (Auteur) In continuous cover forest systems, canopy gaps are created by management activities with an aim of encouraging natural regeneration and of increasing structural heterogeneity. Light Detection and Ranging (LiDAR) may provide a more accurate means to assess gap distribution than ground survey, allowing more effective monitoring. This paper presents a new approach to gap delineation, based on identifying gaps directly from the point cloud and avoiding the need for interpolation of returns to a canopy height model (CHM). Areas of canopy are identified through local maxima identification, filtering and clustering of the point cloud, with gaps subsequently delineated in a GIS environment. When compared to field surveyed gap outlines, the algorithm has an overall accuracy of 88% for data with a high LiDAR point density (11.4 returns per m2) and accuracy of up to 77% for lower density data (1.2 returns per m2). The method provides an increase in overall and Producer's accuracy of 4 and 8% respectively, over a method based on the use of a CHM. The estimation of total gap area is improved by, on average, 16% over the CHM based approach. Results indicate that LiDAR data can be used accurately to delineate gaps in managed forests, potentially allowing more accurate and spatially explicit modelling of understorey light conditions. Copyright Taylor & Francis Numéro de notice : A2010-251 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160903380565 En ligne : https://doi.org/10.1080/01431160903380565 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30445 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-2010031	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt

Estimating crown base height for Scots pine by means of the 3D geometry of airborne laser scanning data / Jari Vauhkonen in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 31 n° 5 (March 2010) . - pp 1213 - 1226 Titre : Estimating crown base height for Scots pine by means of the 3D geometry of airborne laser scanning data Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur Année de publication : 2010 Conférence : Silvilaser 2008, 8th international conference on Lidar applications in forest assessment and inventory 17/09/2008 19/09/2008 Edimbourg Royaume-Uni Proceedings Taylor&Francis Article en page(s) : pp 1213 - 1226 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] croissance des arbres [Termes IGN] données laser [Termes IGN] données localisées 3D [Termes IGN] estimation statistique [Termes IGN] géomètrie algorithmique [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] lasergrammétrie [Termes IGN] modélisation 3D [Termes IGN] Pinus sylvestris [Termes IGN] régression linéaire [Termes IGN] sylviculture [Termes IGN] télémétrie laser aéroporté [Termes IGN] triangulation de Delaunay Résumé : (Auteur) Crown base height (CBH) is an important factor in relation to several characteristics of the tree stock. This paper introduces approaches for estimating tree-level CBH from airborne laser scanning (ALS) data that make use of features of computational geometry. For that purpose, the concepts of Delaunay triangulations and alpha shapes were applied and compared with approaches based on analysing return frequencies and predicting CBH by linear regression. These approaches were evaluated using test data on a total of 185 Scots pine trees, of which 136 were of sawlog size, that were detected and delineated from ALS data with a density of approximately 4 returns m-2. The results suggest that variables based on the frequencies of crown returns within predefined height bins are the most accurate for estimating CBH. By combining the best CBH estimate with the estimated tree height in linear regression, a root mean squared error (RMSE) of 1.4 m (14%) was achieved when all study trees were considered. The estimation was generally less accurate for the trees smaller than those of sawlog size. Although the accuracy of estimating CBH is lower using the three-dimensional (3D) geometry approaches presented here, they are considered to have potential for further development. Numéro de notice : A2010-252 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160903380615 En ligne : https://doi.org/10.1080/01431160903380615 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30446 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-2010031	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt

Uncertainty within satellite LiDAR estimations of vegetation and topography / J. Rosette in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 31 n° 5 (March 2010) . - pp 1325 - 1342 Titre : Uncertainty within satellite LiDAR estimations of vegetation and topography Type de document : Article/Communication Auteurs : J. Rosette, Auteur ; P. North, Auteur ; J. Suarez, Auteur ; S. Los, Auteur Année de publication : 2010 Conférence : Silvilaser 2008, 8th international conference on Lidar applications in forest assessment and inventory 17/09/2008 19/09/2008 Edimbourg Royaume-Uni Proceedings Taylor&Francis Article en page(s) : pp 1325 - 1342 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] altimétrie satellitaire par laser [Termes IGN] canopée [Termes IGN] décomposition de Gauss [Termes IGN] données ICEsat [Termes IGN] forme d'onde [Termes IGN] hauteur des arbres [Termes IGN] modèle de transfert radiatif [Termes IGN] modèle numérique de surface [Termes IGN] pente [Termes IGN] relief Résumé : (Auteur) This paper demonstrates the ability to identify representative ground elevation and vegetation height estimates within the Ice, Cloud and land Elevation Satellite/Geoscience Laser Altimeter System (ICESat/GLAS) waveforms for an area of mixed vegetation and varied topography. Estimating vegetation height within large-footprint Light Detection and Ranging (LiDAR) waveforms relies on the ability to estimate the uppermost canopy surface (signal beginning) and an elevation representing the ground surface, both of which are influenced by vegetation properties and topographic slope. We examined sources of uncertainty for vegetation height estimation from ICESat/GLAS data using airborne LiDAR data, field measurements and the FLIGHT radiative transfer model. In comparison with an independent 10-m resolution digital terrain model (DTM), a method using Gaussian decomposition of the satellite waveform produced a mean bias of -0.10 m when estimating ground elevation. A second method of estimating vegetation height using waveform extent and a terrain index effectively removed slope as an error source but produced a greater ground surface offset (-0.83 m). The two methods of estimating vegetation height compared well with airborne LiDAR estimates (correlation coefficient (R2) = 0.68, root mean square error (RMSE) = 4.4 m and R2 = 0.61, RMSE = 4.9 m, respectively). However, the complex interplay of the structural and optical properties of the intercepted vegetation and slope requires further understanding. A tool such as FLIGHT provides a useful means to explore the sensitivity of the waveform to both vegetation properties and topographic slope. Numéro de notice : A2010-253 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160903380631 En ligne : https://doi.org/10.1080/01431160903380631 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30447 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-2010031	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt