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Forest canopy height estimation using ICESat/GLAS data and error factor analysis in Hokkaido, Japan / Masato Hayashi in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)
[article]
Titre : Forest canopy height estimation using ICESat/GLAS data and error factor analysis in Hokkaido, Japan Type de document : Article/Communication Auteurs : Masato Hayashi, Auteur ; Nobuko Saigusa, Auteur ; Hiroyuki Oguma, Auteur ; Yoshiki Ymagata, Auteur Année de publication : 2013 Article en page(s) : pp 12 - 18 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt
[Termes IGN] hauteur de la végétation
[Termes IGN] Hokkaido (Japon)
[Termes IGN] modèle numérique de surface
[Termes IGN] penteRésumé : (Auteur) Spaceborne light detection and ranging (LiDAR) enables us to obtain information about vertical forest structure directly, and it has often been used to measure forest canopy height or above-ground biomass. However, little attention has been given to comparisons of the accuracy of the different estimation methods of canopy height or to the evaluation of the error factors in canopy height estimation. In this study, we tested three methods of estimating canopy height using the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat), and evaluated several factors that affected accuracy. Our study areas were Tomakomai and Kushiro, two forested areas on Hokkaido in Japan. The accuracy of the canopy height estimates was verified by ground-based measurements. We also conducted a multivariate analysis using quantification theory type I (multiple-regression analysis of qualitative data) and identified the observation conditions that had a large influence on estimation accuracy. The method using the digital elevation model was the most accurate, with a root-mean-square error (RMSE) of 3.2 m. However, GLAS data with a low signal-to-noise ratio (?10.0) and that taken from September to October 2009 had to be excluded from the analysis because the estimation accuracy of canopy height was remarkably low. After these data were excluded, the multivariate analysis showed that surface slope had the greatest effect on estimation accuracy, and the accuracy dropped the most in steeply sloped areas. We developed a second model with two equations to estimate canopy height depending on the surface slope, which improved estimation accuracy (RMSE = 2.8 m). These results should prove useful and provide practical suggestions for estimating forest canopy height using spaceborne LiDAR. Numéro de notice : A2013-385 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32523
in ISPRS Journal of photogrammetry and remote sensing > vol 81 (July 2013) . - pp 12 - 18[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013071 RAB Revue Centre de documentation En réserve L003 Disponible Ground filtering and vegetation mapping using multi-return terrestrial laser scanning / Francesco Pirotti in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)
[article]
Titre : Ground filtering and vegetation mapping using multi-return terrestrial laser scanning Type de document : Article/Communication Auteurs : Francesco Pirotti, Auteur ; A. Guarnieri, Auteur ; Antonio Vettore, Auteur Année de publication : 2013 Article en page(s) : pp 56 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] densité de la végétation
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage de points
[Termes IGN] hauteur de la végétation
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Discriminating laser scanner data points belonging to ground from points above-ground (vegetation or buildings) is a key issue in research. Methods for filtering points into ground and non-ground classes have been widely studied mostly on datasets derived from airborne laser scanners, less so for terrestrial laser scanners. Recent developments in terrestrial laser sensors (longer ranges, faster acquisition and multiple return echoes) has aroused greater interest for surface modelling applications. The downside of TLS is that a typical dataset has high variability in point density, with evident side-effects on processing methods and CPU-time. In this work we use a scan dataset from a sensor which returns multiple target echoes, in this case providing more than 70 million points on our study site. The area presents low, medium and high vegetation, undergrowth with varying density, as well as bare ground with varying morphology (i.e. very steep slopes as well as flat areas). We test an integrated work-flow for defining a terrain and surface model (DTM and DSM) and successively for extracting information on vegetation density and height distribution on such a complex environment. Attention was given to efficiency and speed of processing. The method consists on a first step which subsets the original points to define ground candidates by taking into account the ordinal return number and the amplitude. A custom progressive morphological filter (opening operation) is applied next, on ground candidate points using a multidimensional grid to account for the fallout in point density as a function of distance from scanner. Vegetation density mapping over the area is then estimated using a weighted ratio of point counts in the tri-dimensional space over each cell. The overall result is a pipeline for processing TLS points clouds with minimal user interaction, producing a Digital Terrain Model (DTM), a Digital Surface Model (DSM), a vegetation density map and a derived Canopy Height Model (CHM). These products are of high importance for many applications ranging from forestry to hydrology and geomorphology. Numéro de notice : A2013-092 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.08.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32230
in ISPRS Journal of photogrammetry and remote sensing > vol 76 (February 2013) . - pp 56 - 63[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013021 RAB Revue Centre de documentation En réserve L003 Disponible A multi-scale approach to mapping canopy height / Gordon M. Green in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 2 (February 2013)
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Titre : A multi-scale approach to mapping canopy height Type de document : Article/Communication Auteurs : Gordon M. Green, Auteur ; C. Ahearn, Auteur ; W. Ni-Meister, Auteur Année de publication : 2013 Article en page(s) : pp 185 - 194 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse multiéchelle
[Termes IGN] base de données d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] données altimétriques
[Termes IGN] données ICEsat
[Termes IGN] données laser
[Termes IGN] Etats-Unis
[Termes IGN] fusion de données
[Termes IGN] hauteur de la végétation
[Termes IGN] occupation du sol
[Termes IGN] service web géographiqueRésumé : (Auteur) Mapping vegetation height over large areas presents a problem of scale: height varies with the individual tree or stand, but the resolution of available datasets is too low to characterize this variability sufficiently for many applications. We address this problem by fusing 1 km resolution canopy height data derived from satellite-based laser altimetry with higher-resolution land-cover data, resulting in 30 m resolution estimates of canopy height. These are downscaled further to 1 m resolution by simulating individual trees. A web service architecture is used, which allows processing to occur on demand without preprocessing large datasets. We compared the resulting canopy volumes to reference airborne lidar data from 262 randomly located 1 km2 areas within nine study sites. Results at 30 m resolution show an RMSE of 33 percent of the mean reference volume and an R2 of 0.77; at 1 m the RMSE is 66 percent and the R2 is 0.38. Numéro de notice : A2013-078 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.79.2.185 En ligne : https://doi.org/10.14358/PERS.79.2.185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32216
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 2 (February 2013) . - pp 185 - 194[article]The electronically steerable flash Lidar : A full waveform scanning system for topographic and ecosystem structure applications / H. Duong in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 2 (November 2012)
[article]
Titre : The electronically steerable flash Lidar : A full waveform scanning system for topographic and ecosystem structure applications Type de document : Article/Communication Auteurs : H. Duong, Auteur Année de publication : 2012 Article en page(s) : pp 4809 - 4820 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tempérée
[Termes IGN] forêt tropicale
[Termes IGN] forme d'onde pleine
[Termes IGN] hauteur de la végétation
[Termes IGN] Lidar
[Termes IGN] Texas (Etats-Unis)Résumé : (Auteur) The electronically steerable flash lidar (ESFL) is a waveform lidar sensor that incorporates two advances relevant to the design of future spaceborne lidar sensors. The first is a nonmechanical scanner that splits a single incoming beam into a variable number of output beams that can be aligned independently across track; the transmitted beam pattern can be changed up to 60 Hz. The second is a flash focal plane array (FFPA) capable of recording waveforms simultaneously from a 128 x 128 pixel grid with individual footprints spread over multiple pixels. In this paper, the incoming beam was used to illuminate eight 8.4-m footprints which were imaged simultaneously on 12 x 12 pixel subsets of the FFPA. The FFPA digitizes waveforms at a vertical resolution of 75 cm over 41 vertical bins to create waveforms of 30.75-m depth. Multiple waveforms obtained using range-gating were combined for these analyses. ESFL data were collected at Manitou Experimental Forest (MEF), located in the Pikes Peak National Forest, Colorado, USA and the Stephen F. Austin Experimental Forest (AEF), located in the Angelina Forest, Nacogdoches, TX. We evaluated the use of individual pixel-level and aggregated footprint-level waveforms and alternate approaches to define the extent of each footprint in the focal plane array. Using discrete return lidar data as a reference, we evaluated the ability of ESFL lidar to estimate canopy height and compared the two sensors' rates of penetration to the terrain surface. We found the footprint-level waveforms were better suited for use with existing waveform processing techniques, although techniques for processing at the pixel-level appear feasible. Relationships between height estimates from each lidar data set were most closely related when footprint-level ESFL waveforms were calculated after removing pixels that had less than 50% of the maximum energy within that footprint. Regressions between ESFL and reference lidar data estimates - f height explained 84% (AEF) and 85% (MEF) of variance; this study could not say definitively which method yielded the more accurate estimate of height. Numéro de notice : A2012-593 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2193588 Date de publication en ligne : 16/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2193588 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32039
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 2 (November 2012) . - pp 4809 - 4820[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012111B RAB Revue Centre de documentation En réserve L003 Disponible 3-D mapping of a multi-layered Mediterranean forest using ALS data / António Ferraz in Remote sensing of environment, vol 121 (June 2012)
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Titre : 3-D mapping of a multi-layered Mediterranean forest using ALS data Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Frédéric Bretar, Auteur ; Stéphane Jacquemoud, Auteur ; Gil Rito-Gonçalves , Auteur ; Luisa Pereira, Auteur ; Margarida Tomé, Auteur ; Paola Soares, Auteur Année de publication : 2012 Article en page(s) : pp 210 - 223 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de décalage moyen
[Termes IGN] biomasse (combustible)
[Termes IGN] carte en 3D
[Termes IGN] cartographie 3D
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Eucalyptus globulus
[Termes IGN] forêt méditerranéenne
[Termes IGN] hauteur de la végétation
[Termes IGN] Pinus pinaster
[Termes IGN] Portugal
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] strate végétaleRésumé : (Auteur) This study presents a robust approach for characterization of multi-layered forests using airborne laser scanning (ALS) data. Fuel mapping or biomass estimation requires knowing the diversity and boundaries of the forest patches, as well as their spatial pattern. This includes the thickness of the main vegetation layers, but also the spatial arrangement and size of the individual plants that compose each stratum. In order to decompose the ALS point cloud into genuine 3-D segments corresponding to individual vegetation features, such as shrubs or tree crowns, we apply a statistical approach based on the mean shift algorithm. The segments are progressively assigned to a forest layer: ground vegetation, understory or overstory. Our method relies on a single biophysically meaningful parameter, the kernel bandwidth, which is related to the local forest structure. It is validated on 44 plots of a Portuguese forest, composed mainly of eucalyptus (Eucalyptus globulus Labill.) and maritime pine (Pinus pinaster Ait.) trees. The number of detected trees varies with the dominance position: from 98.6% for the dominant trees to 12.8% for the suppressed trees. Linear regression models explain up to 70% of the variability associated with ground vegetation and understory height. Numéro de notice : A2012-730 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2012.01.020 Date de publication en ligne : 03/03/2012 En ligne : https://doi.org/10.1016/j.rse.2012.01.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91079
in Remote sensing of environment > vol 121 (June 2012) . - pp 210 - 223[article]Small-footprint Lidar estimations of sagebrush canopy characteristics / J. Mitchell in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 5 (May 2011)Permalink