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Empirical study of variation in lidar point density over different land covers

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Empirical study of variation in lidar point density over different land covers

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dc.contributor.author Balsa Barreiro, José es_ES
dc.contributor.author Lerma García, José Luis es_ES
dc.date.accessioned 2015-12-30T09:19:47Z
dc.date.available 2015-12-30T09:19:47Z
dc.date.issued 2014-04
dc.identifier.issn 0143-1161
dc.identifier.uri http://hdl.handle.net/10251/59299
dc.description This is an author's accepted manuscript of an article published in International Journal of Remote Sensing; Volume 35, Issue 9, 2014 ; copyright Taylor & Francis, available online at: http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.903355 es_ES
dc.description.abstract Point density in airborne lidar surveys is one of the key parameters that influence not only the accuracy of generated DSM/DEM but also processing and costs. Point density variations occur (independently of keeping constant flight parameters) throughout the survey depending on the topography, the land cover, and the laser scanning mechanism. In this article, variations in point density across different land covers are analysed with an airborne oscillating mirror laser scanner. A wide group of samples from the different land covers is taken from single flight strips over level ground in order to minimize the effect of topography. The influence of the oscillating mirror laser scanner system is also minimized considering points along the central swath area. Mean values for each land cover are established regarding ground point density and first pulse returns. Significant differences in both raw points as well as on-the-ground points are registered, mainly due to the presence of features over the ground and the degree of opacity thereof. Regarding ground points, the relative differences between the two software packages used are 5% approximately. Significant point density differences can be found among the six analysed land covers. Furthermore, extrapolated pulse rate increments are presented to fulfil lidar specifications that neglect land cover as an input parameter to satisfy ground point density values, namely in non-overlapping areas. es_ES
dc.language Inglés es_ES
dc.publisher Taylor & Francis: STM, Behavioural Science and Public Health Titles es_ES
dc.relation.ispartof International Journal of Remote Sensing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject LIDAR es_ES
dc.subject Point density es_ES
dc.subject Land covers es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Empirical study of variation in lidar point density over different land covers es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/01431161.2014.903355
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.description.bibliographicCitation Balsa Barreiro, J.; Lerma García, JL. (2014). Empirical study of variation in lidar point density over different land covers. International Journal of Remote Sensing. 35(9):3372-3383. doi:10.1080/01431161.2014.903355 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1080/01431161.2014.903355 es_ES
dc.description.upvformatpinicio 3372 es_ES
dc.description.upvformatpfin 3383 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 35 es_ES
dc.description.issue 9 es_ES
dc.relation.senia 281320 es_ES
dc.description.references Anderson, E. S., Thompson, J. A., & Austin, R. E. (2005). LIDAR density and linear interpolator effects on elevation estimates. International Journal of Remote Sensing, 26(18), 3889-3900. doi:10.1080/01431160500181671 es_ES
dc.description.references Anderson, E. S., Thompson, J. A., Crouse, D. A., & Austin, R. E. (2006). Horizontal resolution and data density effects on remotely sensed LIDAR-based DEM. Geoderma, 132(3-4), 406-415. doi:10.1016/j.geoderma.2005.06.004 es_ES
dc.description.references Artuso, R., S. Bovet, and A. Streilein. 2003. “Practical Methods for the Verification of Countrywide Produced Terrain and Surface Models.” International Archives of Photogrammetry and Remote Sensing, IAPRS, vol. XXXIV (3/W13), 14–19. Dresden, October 8–10. es_ES
dc.description.references Axelsson, P. 2000. “DEM Generation from Laser Scanner Data Using Adaptative TIN Models.” International Archives of Photogrammetry and Remote Sensing, IAPRS, Amsterdam, Netherlands, vol. XXXIII (B4/1), 110–117, Amsterdam, July 16–22. es_ES
dc.description.references Balsa-Barreiro, J., & Lerma, J. L. (2014). A new methodology to estimate the discrete-return point density on airborne lidar surveys. International Journal of Remote Sensing, 35(4), 1496-1510. doi:10.1080/01431161.2013.878063 es_ES
dc.description.references Balsa-Barreiro, J. (2012). Airborne light detection and ranging (LiDAR) point density analysis. Scientific Research and Essays, 7(33). doi:10.5897/sre12.278 es_ES
dc.description.references Baltsavias, E. P. (1999). Airborne laser scanning: existing systems and firms and other resources. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2-3), 164-198. doi:10.1016/s0924-2716(99)00016-7 es_ES
dc.description.references Heidemann, H. K. 2012. “Lidar Base Specification (Version 1.0).” InU.S. Geological Survey Techniques and Methods, Book 11, Chap. B4, 63p. Reston, VA: USGS. es_ES
dc.description.references Hodgson, M. E., & Bresnahan, P. (2004). Accuracy of Airborne Lidar-Derived Elevation. Photogrammetric Engineering & Remote Sensing, 70(3), 331-339. doi:10.14358/pers.70.3.331 es_ES
dc.description.references Liu, X., Z. Zhang, J. Peterson, and S. Chandra. 2007. “The Effect of LiDAR Data Density on DEM Accuracy.” InInternational Congress on Modelling and Simulation: Land, Water and Environmental Management: Integrated Systems for Sustainability, December 10–13, 1363–1369. Christchurch: Modelling and Simulation Society of Australia and New Zealand. es_ES
dc.description.references Raber, G. 2003. “The Effect of LiDAR Posting Density on DEM Accuracy and Flood Extent Delineation: A GIS-Simulation Approach.” InProceedings of the UCGIS Summer Assembly, June 17–19, 34pp, Pacific Grove, CA: United Consortium for Geographic Information Science (UCGIS). es_ES
dc.description.references Raber, G. T., Jensen, J. R., Hodgson, M. E., Tullis, J. A., Davis, B. A., & Berglund, J. (2007). Impact of Lidar Nominal Post-spacing on DEM Accuracy and Flood Zone Delineation. Photogrammetric Engineering & Remote Sensing, 73(7), 793-804. doi:10.14358/pers.73.7.793 es_ES
dc.description.references Reutebuch, S. E., McGaughey, R. J., Andersen, H.-E., & Carson, W. W. (2003). Accuracy of a high-resolution lidar terrain model under a conifer forest canopy. Canadian Journal of Remote Sensing, 29(5), 527-535. doi:10.5589/m03-022 es_ES
dc.description.references Su, J., & Bork, E. (2006). Influence of Vegetation, Slope, and Lidar Sampling Angle on DEM Accuracy. Photogrammetric Engineering & Remote Sensing, 72(11), 1265-1274. doi:10.14358/pers.72.11.1265 es_ES
dc.description.references Tesfamichael, S. G., Ahmed, F. B., & Van Aardt, J. A. N. (2010). Investigating the impact of discrete-return lidar point density on estimations of mean and dominant plot-level tree height in Eucalyptus grandis plantations. International Journal of Remote Sensing, 31(11), 2925-2940. doi:10.1080/01431160903144086 es_ES
dc.description.references Triglav-Čekada, M., Crosilla, F., & Kosmatin-Fras, M. (2009). A Simplified Analytical Model for a-priori Lidar Point-positioning Error Estimation and a Review of Lidar Error Sources. Photogrammetric Engineering & Remote Sensing, 75(12), 1425-1439. doi:10.14358/pers.75.12.1425 es_ES
dc.description.references Wang, Y., Weinacker, H., & Koch, B. (2008). A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest. Sensors, 8(6), 3938-3951. doi:10.3390/s8063938 es_ES
dc.description.references Watershed Sciences, Inc. 2010.Minimum LiDAR considerations in the Pacific Northwest. Accessed April 1, 2014. http://www.oregongeology.org/sub/projects/olc/minimum-lidar-data-density.pdf. es_ES
dc.description.references Wehr, A., & Lohr, U. (1999). Airborne laser scanning—an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2-3), 68-82. doi:10.1016/s0924-2716(99)00011-8 es_ES
dc.description.references Yu, X., J. Hyyppä, H. Hyyppä, and M. Maltamo. 2004. “Effects of Flight Altitude on Tree Height Estimation Using Airborne Laser Scanning.” InInternational Conference NATSCAN International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, October 3–6, vol. XXXVI (8/W2), 96–101. Freiburg: IAPRS. es_ES
dc.description.references Yu, X., H. Hyyppä, H. Kaartinen, J. Hyyppä, E. Ahokas, and S. Kaasalainen. 2005. “Applicability of First Pulse Derived Digital Terrain Models for Boreal Forest Studies.” ISPRS Workshop Laser scanning, WG III/3, III/4, V/3, 97–102, Enschede, September 12–14. es_ES


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