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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]

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Intercalibration of vegetation indices from different sensor systems / M.D. Steven in Remote sensing of environment, vol 88 n° 4 (30/12/2003)  

Public [article]  inRemote sensing of environment > vol 88 n° 4 (30/12/2003) . - pp 412 - 422 Titre : Intercalibration of vegetation indices from different sensor systems Type de document : Article/Communication Auteurs : M.D. Steven, Auteur ; T.J. Malthus, Auteur ; F. Baret, Auteur ; H. Xu, Auteur ; M. Chopping, Auteur Année de publication : 2003 Article en page(s) : pp 412 - 422 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] données multicapteurs [Termes IGN] indice de végétation [Termes IGN] luminance lumineuse [Termes IGN] réflectance végétale [Termes IGN] simulation d'étalonnage Résumé : (Auteur) Spectroradiometric measurements were made over a range of crop canopy densities, soil backgrounds and foliage colour. The reflected spectral radiances were convoluted with the spectral response functions of a range of satellite instruments to simulate their responses. When Normalised Difference Vegetation Indices (NDVI) from the different instruments were compared, they varied by a few percent, but the values were strongly linearly related, allowing vegetation indices from one instrument to be intercalibrated against another. A table of conversion coefficents is presented for AVHRR, ATSR2, Landsat MSS, TM and ETM+, SPOT-2 and SPOT-4 HRV, IRS, IKONOS, SEAWIFS, MISR, MODIS, POLDER, Quickbird and MERIS (see Appendix A for glossary of acronyms). The same set of coefficients was found to apply, within the margin of error of the analysis, for the Soil Adjusted Vegetation Index SAVI. The relationships for SPOT vs. TM and for ATSR-2 vs. AVHRR were directly validated by comparison of atmospherically corrected image data. The results indicate that vegetation indices can be interconverted to a precision of 12%. This result offers improved opportunities for monitoring crops through the growing season and the prospects of better continuity of long-term monitoring of vegetation responses to environmental change. Numéro de notice : A2003-367 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.08.010 En ligne : https://doi.org/10.1016/j.rse.2003.08.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26447 [article]