Skip to main content
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 3
  • Cited by
    This chapter has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Li, Zhenlong Hodgson, Michael E. and Li, Wenwen 2018. A general-purpose framework for parallel processing of large-scale LiDAR data. International Journal of Digital Earth, Vol. 11, Issue. 1, p. 26.

    Robinson, Sarah E. Bohon, Wendy Kleber, Emily J. Arrowsmith, J Ramón and Crosby, Christopher J. 2017. Applications of high-resolution topography in Earth science education. Geosphere, Vol. 13, Issue. 6, p. 1887.

    Carter, William E. Glennie, Craig L. and Shrestha, Ramesh L. 2015. IAG 150 Years. Vol. 143, Issue. , p. 399.

  • Print publication year: 2011
  • Online publication date: October 2011

16 - Online access and processing of LiDAR topography data

from Part V - Web services and scientific workflows


Real-time sensor networks, space and airborne-based remote sensing, real-time geodesy and seismology, massive geospatial databases, and large computational models are all enabling new and exciting research on the forefront of the earth sciences. However, with these technologies comes a prodigious increase in the volume and complexity of scientific data that must be efficiently managed, archived, distributed, processed, and integrated in order for it to be of use to the scientific community. Data volume, processing expertise, or computing resource requirements may be a barrier to the scientific community's access to and effective use of these datasets. An emerging solution is a shared cyberinfrastructure that provides access to data, tools, and computing resources. A key objective of geoinformatics initiatives (e.g., Sinha, 2000) is to build such cyberinfrastructure for the geosciences through collaboration between earth scientists and computer scientists.

Airborne LiDAR (Light Distance And Ranging) data have emerged as one of the most powerful tools available for documenting the Earth's topography and its masking vegetation at high resolution (defined here as pixel dimensions less than 2 meters). LiDAR-derived digital elevation models (DEMs) are typically of a resolution more than an order of magnitude better than the best-available 10-meter DEMs. The ability to use these data to construct 2.5-D and 3-D models of the Earth's topography and vegetation is rapidly making them an indispensable tool for earth science research (e.g., Carter et al., 2001).

Recommend this book

Email your librarian or administrator to recommend adding this book to your organisation's collection.

  • Online ISBN: 9780511976308
  • Book DOI:
Please enter your name
Please enter a valid email address
Who would you like to send this to *
,ASPRS: American Society for Photogrammetry and Remote Sensing (2009). LAS 1.3 Format Specification, July 14, 2009,
Carter, W. E., Shrestha, R. L., Tuell, G., Bloomquist, D., and Sartori, M. (2001). Airborne laser swath mapping shines new light on Earth's topography. Eos TransactionsAGU, 82: 549–550, 555.
,Committee on Challenges and Opportunities in Earth Surface Processes (2010). Landscapes on the Edge: New Horizons for Research on Earth's Surface. Washington, D.C.: National Research Council, 180pp.
Haala, N. and Brenner, C. (1999). Extraction of buildings and trees in urban environments. ISPRS Journal of Photogrammetry & Remote Sensing, 54: 130–137.
Harding, D. J. (2006). Overview of NASA Airborne and Satellite Laser Altimeters and Commercial Analysis Software, 2006 UNAVCO Science Workshop, Boulder, CO, USA. Original presentation at
Haugerud, R. A. and Harding, D. J. (2001). Some algorithms for virtual deforestation (VDF) of LIDAR topographic survey data. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIV-3/W4, pp. 211–217.
Haugerud, R. A., Harding, D. J., Mark, L. al. (2004). Lidar measurement of topographic change during the 2004 eruption of Mount St. Helens, WA. Eos Transactions AGU, 85(47), Fall Meet. Suppl., Abstract V53D-01A.
Jaeger-Frank, E., Crosby, C. J., Memon, al. (2006). A three tier architecture for LiDAR interpolation and analysis. LNCS3993. Berlin: Springer, pp. 920–927, doi:10.1007/11758532_123
Kim, H., Arrowsmith, J. R., Crosby, C. al. (2006). An efficient implementation of a local binning algorithm for digital elevation model generation of LiDAR/ALSM dataset. Eos Transactions AGU, 87(52), Fall Meet. Suppl., Abstract G53C-0921.
Lefsky, M. A., Cohen, W. B., Parker, G. G., and Harding, D. J. (2002). Lidar remote sensing for ecosystem studies. Bioscience, 52: 19–30.
Ludäscher, B., Altintas, I., Berkley, al. (2005). Scientific workflow management and the Kepler system. Concurrency and Computation: Practice & Experience, Special Issue on Scientific Workflows, 18(10): 1039–1065.
Maas, H.-G. and Vosselman, G. (1999). Two algorithms for extracting building models from raw laser altimetry data. ISPRS Journal of Photogrammetry & Remote Sensing, 54: 153–163.
Mitas, L. and Mitasova, H. (1999). Spatial interpolation, In Geographical Information Systems: Principles, Techniques, Management and Applications, ed. Longley, P., Goodchild, M. F., Maguire, D. J. and Rhind, D. W.. New York: Wiley, pp. 481–492.
Mitasova, H. and Hofierka, J. (1993). Interpolation by regularized spline with tension II: Application to terrain modeling and surface geometry analysis. Mathematical Geology, 25: 657–667.
Mitasova, H. and Mitas, L. (1993). Interpolation by regularized spline with tension: I. Theory and implementation. Mathematical Geology, 25: 641–655.
Nandigam, V., Baru, C., and Crosby, C. J. (2010). Database design for high-resolution LIDAR topography data. In SSDBM 2010, ed. Gertz, M. and Ludascher, B.. LNCS 6187. Berlin: Springer, pp. 151–159.
Neteler, M. and Mitasova, H. (2004). Open Source GIS: A GRASS GIS Approach, 2nd edn. Kluwer International Series in Engineering and Computer Science, 773.Dordrecht, The Netherlands: Kluwer Academic Press/Springer, 424pp.
,North Carolina Floodplain Mapping Program (2000). About the North Carolina Floodplain Mapping Program,
Owens, T. J. and Keller, G. R. (2003). GEON (GEOscience Network): A first step in creating cyberinfrastructure for the geosciences. Electronic Seismologist, 74(4).
Perron, J. T., Kirchner, J. W., and Dietrich, W. E. (2009). Formation of evenly spaced ridges and valleys. Nature, 460: doi:10.1038/nature08174.
Roering, J. J., Kirchner, J. W., and Dietrich, W. E. (1999) Evidence for nonlinear, diffusive sediment transport on hillslopes and implications for landscape morphology. Water Resources Research, 35: 853–580.
Sallenger, A. H., Krabill, W., Swift, al. (2003). Evaluation of airborne scanning LiDAR for coastal change applications. Journal of Coastal Research, 19(1): 125–133.
Shan, S., Bevis, M., Kendrick, al. (2007). Kinematic GPS solutions for aircraft trajectories: Identifying and minimizing systematic height errors associated with atmospheric propagation delays. Geophysical Research Letters, 34, L23S07, doi:10.1029/2007GL030889.
Shrestha, R. L., Carter, W. E., Lee, M., Finer, P., and Sartori, M. (1999). Airborne laser swath mapping: Accuracy assessment for surveying and mapping applications. Journal of American Congress on Surveying and Mapping, 59: 83–94.
Sinha, A. K. (2000,). Geoinformatics: A Defining Opportunity for Earth Science Research. White Paper Submitted to the National Science Foundation,
Sithole, G. and Vosselman, G. (2004). Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds. ISPRS Journal of Photogrammetry & Remote Sensing, 59: 85–101.
Stoker, J. M., Greenlee, S. K., Gesch, D. B., and Menig, J. C. (2006). CLICK: The new USGS Center for LiDAR Information and Knowledge. Photogrammetric Engineering & Remote Sensing, 27: 613–616.
,U.S. Army Topographic Engineering Center Topography, Imagery and Geospatial Research Division Data Representation Branch (2006). Survey of Terrain Visualization Software,
Zielke, O., Arrowsmith, J. R., Grant Ludwig, L., and Akciz, S. O. (2010). Slip in the 1857 and earlier large earthquakes along the Carrizo Plain, San Andreas Fault. Science, doi:10.1126/science.1182781.